04_Predictions.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "05a278d6",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import cv2\n",
    "import pytesseract\n",
    "from glob import glob\n",
    "import spacy\n",
    "import re\n",
    "import string\n",
    "\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "df864592",
   "metadata": {},
   "outputs": [],
   "source": [
    "def clean_text(txt):\n",
    "    whitespace = string.whitespace\n",
    "    punctuation = '!#$%&\\'()*+:;<=>?[\\\\]^`{|}~'\n",
    "    tableWhiteSpace = str.maketrans(\"\", \"\", whitespace)\n",
    "    tablePunctuation = str.maketrans(\"\", \"\", punctuation)\n",
    "    text = str(txt)\n",
    "    text = text.lower()\n",
    "    removewhitespace = text.translate(tableWhiteSpace)\n",
    "    removepunctuation = removewhitespace.translate(tablePunctuation)\n",
    "    \n",
    "    return str(removepunctuation)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4be40f54",
   "metadata": {},
   "source": [
    "### STEPS\n",
    "\n",
    "Load Image\n",
    "\n",
    "Extract Data from Text using Pytesseract\n",
    "\n",
    "Convert Data into Content\n",
    "\n",
    "Get Predictions from NER Model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "4300c305",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Load NER Model\n",
    "model_ner = spacy.load(\"output/model-best/\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "f38f4784",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(-0.5, 706.5, 436.5, -0.5)"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Load Image\n",
    "\n",
    "#image = cv2.imread(\"data/Selected/051.jpeg\")\n",
    "#image = cv2.imread(\"data/Selected/031.jpeg\")\n",
    "image = cv2.imread(\"data/Selected/053.jpeg\")\n",
    "\n",
    "                   \n",
    "plt.imshow(image)\n",
    "plt.axis(\"off\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "ef72b1ad",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "level\tpage_num\tblock_num\tpar_num\tline_num\tword_num\tleft\ttop\twidth\theight\tconf\ttext\n",
      "1\t1\t0\t0\t0\t0\t0\t0\t707\t437\t-1\t\n",
      "2\t1\t1\t0\t0\t0\t72\t84\t509\t42\t-1\t\n",
      "3\t1\t1\t1\t0\t0\t72\t84\t509\t42\t-1\t\n",
      "4\t1\t1\t1\t1\t0\t110\t84\t471\t25\t-1\t\n",
      "5\t1\t1\t1\t1\t1\t110\t84\t74\t19\t96\tJames\n",
      "5\t1\t1\t1\t1\t2\t193\t84\t61\t18\t96\tBond\n",
      "5\t1\t1\t1\t1\t3\t365\t84\t60\t19\t96\tYour\n",
      "5\t1\t1\t1\t1\t4\t434\t84\t53\t25\t96\tCity\n",
      "5\t1\t1\t1\t1\t5\t496\t84\t85\t19\t96\tHonda\n",
      "4\t1\t1\t1\t2\t0\t72\t109\t221\t17\t-1\t\n",
      "5\t1\t1\t1\t2\t1\t72\t109\t40\t13\t93\tSales\n",
      "5\t1\t1\t1\t2\t2\t119\t109\t14\t13\t59\t&\n",
      "5\t1\t1\t1\t2\t3\t138\t110\t62\t16\t96\tLeasing\n",
      "5\t1\t1\t1\t2\t4\t206\t109\t87\t13\t96\tConsultant\n",
      "2\t1\t2\t0\t0\t0\t371\t219\t214\t129\t-1\t\n",
      "3\t1\t2\t1\t0\t0\t371\t219\t214\t129\t-1\t\n",
      "4\t1\t2\t1\t1\t0\t372\t219\t188\t13\t-1\t\n",
      "5\t1\t2\t1\t1\t1\t372\t220\t41\t12\t96\t4718\n",
      "5\t1\t2\t1\t1\t2\t419\t219\t29\t13\t95\tSan\n",
      "5\t1\t2\t1\t1\t3\t454\t220\t75\t12\t95\tFernando\n",
      "5\t1\t2\t1\t1\t4\t535\t220\t25\t12\t90\tRd.\n",
      "4\t1\t2\t1\t2\t0\t372\t242\t162\t14\t-1\t\n",
      "5\t1\t2\t1\t2\t1\t372\t242\t75\t14\t94\tGlendale,\n",
      "5\t1\t2\t1\t2\t2\t454\t242\t24\t13\t94\tCA\n",
      "5\t1\t2\t1\t2\t3\t484\t242\t50\t13\t94\t91204\n",
      "4\t1\t2\t1\t3\t0\t371\t264\t169\t15\t-1\t\n",
      "5\t1\t2\t1\t3\t1\t371\t264\t34\t13\t96\tBus.\n",
      "5\t1\t2\t1\t3\t2\t413\t264\t41\t15\t96\t(818)\n",
      "5\t1\t2\t1\t3\t3\t460\t264\t80\t13\t96\t547-4220\n",
      "4\t1\t2\t1\t4\t0\t372\t287\t166\t15\t-1\t\n",
      "5\t1\t2\t1\t4\t1\t372\t287\t31\t13\t96\tFax,\n",
      "5\t1\t2\t1\t4\t2\t410\t287\t41\t15\t96\t(818)\n",
      "5\t1\t2\t1\t4\t3\t458\t287\t80\t13\t96\t547-4680\n",
      "4\t1\t2\t1\t5\t0\t372\t308\t213\t18\t-1\t\n",
      "5\t1\t2\t1\t5\t1\t372\t308\t213\t18\t84\tinfo@FirstPrintingCA.com\n",
      "4\t1\t2\t1\t6\t0\t371\t332\t211\t16\t-1\t\n",
      "5\t1\t2\t1\t6\t1\t371\t332\t211\t16\t63\twww.FirstPrintingCA.com\n",
      "2\t1\t3\t0\t0\t0\t24\t24\t651\t382\t-1\t\n",
      "3\t1\t3\t1\t0\t0\t24\t24\t651\t382\t-1\t\n",
      "4\t1\t3\t1\t1\t0\t24\t24\t651\t382\t-1\t\n",
      "5\t1\t3\t1\t1\t1\t24\t24\t651\t382\t95\t \n",
      "\n"
     ]
    }
   ],
   "source": [
    "# Extract Data from Text using Pytesseract\n",
    "\n",
    "tess_data = pytesseract.image_to_data(image)\n",
    "print(tess_data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "0132a4bf",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>level</th>\n",
       "      <th>page_num</th>\n",
       "      <th>block_num</th>\n",
       "      <th>par_num</th>\n",
       "      <th>line_num</th>\n",
       "      <th>word_num</th>\n",
       "      <th>left</th>\n",
       "      <th>top</th>\n",
       "      <th>width</th>\n",
       "      <th>height</th>\n",
       "      <th>conf</th>\n",
       "      <th>text</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>2</td>\n",
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       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>371</td>\n",
       "      <td>219</td>\n",
       "      <td>214</td>\n",
       "      <td>129</td>\n",
       "      <td>-1</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>371</td>\n",
       "      <td>219</td>\n",
       "      <td>214</td>\n",
       "      <td>129</td>\n",
       "      <td>-1</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>372</td>\n",
       "      <td>219</td>\n",
       "      <td>188</td>\n",
       "      <td>13</td>\n",
       "      <td>-1</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>372</td>\n",
       "      <td>220</td>\n",
       "      <td>41</td>\n",
       "      <td>12</td>\n",
       "      <td>96</td>\n",
       "      <td>4718</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>419</td>\n",
       "      <td>219</td>\n",
       "      <td>29</td>\n",
       "      <td>13</td>\n",
       "      <td>95</td>\n",
       "      <td>san</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>454</td>\n",
       "      <td>220</td>\n",
       "      <td>75</td>\n",
       "      <td>12</td>\n",
       "      <td>95</td>\n",
       "      <td>fernando</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>535</td>\n",
       "      <td>220</td>\n",
       "      <td>25</td>\n",
       "      <td>12</td>\n",
       "      <td>90</td>\n",
       "      <td>rd.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
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       "      <td>0</td>\n",
       "      <td>372</td>\n",
       "      <td>242</td>\n",
       "      <td>162</td>\n",
       "      <td>14</td>\n",
       "      <td>-1</td>\n",
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      "text/plain": [
       "   level page_num block_num par_num line_num word_num left  top width height  \\\n",
       "14     2        1         2       0        0        0  371  219   214    129   \n",
       "15     3        1         2       1        0        0  371  219   214    129   \n",
       "16     4        1         2       1        1        0  372  219   188     13   \n",
       "17     5        1         2       1        1        1  372  220    41     12   \n",
       "18     5        1         2       1        1        2  419  219    29     13   \n",
       "19     5        1         2       1        1        3  454  220    75     12   \n",
       "20     5        1         2       1        1        4  535  220    25     12   \n",
       "21     4        1         2       1        2        0  372  242   162     14   \n",
       "\n",
       "   conf      text  \n",
       "14   -1            \n",
       "15   -1            \n",
       "16   -1            \n",
       "17   96      4718  \n",
       "18   95       san  \n",
       "19   95  fernando  \n",
       "20   90       rd.  \n",
       "21   -1            "
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Convert into DataFrame\n",
    "tessList = list(map(lambda x: x.split(\"\\t\"), tess_data.split(\"\\n\")))\n",
    "\n",
    "df = pd.DataFrame(tessList[1:], columns=tessList[0])\n",
    "\n",
    "# remove missing values\n",
    "df.dropna(inplace=True)\n",
    "\n",
    "# clean text\n",
    "df[\"text\"] = df[\"text\"].apply(clean_text)\n",
    "\n",
    "df[14:22]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "16e9f2db",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "james bond your city honda sales leasing consultant 4718 san fernando rd. glendale, ca 91204 bus. 818 547-4220 fax, 818 547-4680 info@firstprintingca.com www.firstprintingca.com\n"
     ]
    }
   ],
   "source": [
    "# Convert Data into Content\n",
    "df_clean = df.query(\"text != ''\")\n",
    "content = \" \".join([w for w in df_clean[\"text\"]]) # it will take and join each word by one space\n",
    "print(content)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "84268473",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "D:\\ANACONDA\\envs\\docscanner\\lib\\site-packages\\spacy\\displacy\\__init__.py:103: UserWarning: [W011] It looks like you're calling displacy.serve from within a Jupyter notebook or a similar environment. This likely means you're already running a local web server, so there's no need to make displaCy start another one. Instead, you should be able to replace displacy.serve with displacy.render to show the visualization.\n",
      "  warnings.warn(Warnings.W011)\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<span class=\"tex2jax_ignore\"><!DOCTYPE html>\n",
       "<html lang=\"en\">\n",
       "    <head>\n",
       "        <title>displaCy</title>\n",
       "    </head>\n",
       "\n",
       "    <body style=\"font-size: 16px; font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', Helvetica, Arial, sans-serif, 'Apple Color Emoji', 'Segoe UI Emoji', 'Segoe UI Symbol'; padding: 4rem 2rem; direction: ltr\">\n",
       "<figure style=\"margin-bottom: 6rem\">\n",
       "<div class=\"entities\" style=\"line-height: 2.5; direction: ltr\">\n",
       "<mark class=\"entity\" style=\"background: #ddd; padding: 0.45em 0.6em; margin: 0 0.25em; line-height: 1; border-radius: 0.35em;\">\n",
       "    james\n",
       "    <span style=\"font-size: 0.8em; font-weight: bold; line-height: 1; border-radius: 0.35em; vertical-align: middle; margin-left: 0.5rem\">B-NAME</span>\n",
       "</mark>\n",
       " \n",
       "<mark class=\"entity\" style=\"background: #ddd; padding: 0.45em 0.6em; margin: 0 0.25em; line-height: 1; border-radius: 0.35em;\">\n",
       "    bond\n",
       "    <span style=\"font-size: 0.8em; font-weight: bold; line-height: 1; border-radius: 0.35em; vertical-align: middle; margin-left: 0.5rem\">I-NAME</span>\n",
       "</mark>\n",
       " \n",
       "<mark class=\"entity\" style=\"background: #ddd; padding: 0.45em 0.6em; margin: 0 0.25em; line-height: 1; border-radius: 0.35em;\">\n",
       "    your\n",
       "    <span style=\"font-size: 0.8em; font-weight: bold; line-height: 1; border-radius: 0.35em; vertical-align: middle; margin-left: 0.5rem\">B-ORG</span>\n",
       "</mark>\n",
       " \n",
       "<mark class=\"entity\" style=\"background: #ddd; padding: 0.45em 0.6em; margin: 0 0.25em; line-height: 1; border-radius: 0.35em;\">\n",
       "    city\n",
       "    <span style=\"font-size: 0.8em; font-weight: bold; line-height: 1; border-radius: 0.35em; vertical-align: middle; margin-left: 0.5rem\">I-ORG</span>\n",
       "</mark>\n",
       " \n",
       "<mark class=\"entity\" style=\"background: #ddd; padding: 0.45em 0.6em; margin: 0 0.25em; line-height: 1; border-radius: 0.35em;\">\n",
       "    honda\n",
       "    <span style=\"font-size: 0.8em; font-weight: bold; line-height: 1; border-radius: 0.35em; vertical-align: middle; margin-left: 0.5rem\">I-ORG</span>\n",
       "</mark>\n",
       " \n",
       "<mark class=\"entity\" style=\"background: #ddd; padding: 0.45em 0.6em; margin: 0 0.25em; line-height: 1; border-radius: 0.35em;\">\n",
       "    sales\n",
       "    <span style=\"font-size: 0.8em; font-weight: bold; line-height: 1; border-radius: 0.35em; vertical-align: middle; margin-left: 0.5rem\">B-DES</span>\n",
       "</mark>\n",
       " \n",
       "<mark class=\"entity\" style=\"background: #ddd; padding: 0.45em 0.6em; margin: 0 0.25em; line-height: 1; border-radius: 0.35em;\">\n",
       "    leasing\n",
       "    <span style=\"font-size: 0.8em; font-weight: bold; line-height: 1; border-radius: 0.35em; vertical-align: middle; margin-left: 0.5rem\">I-DES</span>\n",
       "</mark>\n",
       " \n",
       "<mark class=\"entity\" style=\"background: #ddd; padding: 0.45em 0.6em; margin: 0 0.25em; line-height: 1; border-radius: 0.35em;\">\n",
       "    consultant\n",
       "    <span style=\"font-size: 0.8em; font-weight: bold; line-height: 1; border-radius: 0.35em; vertical-align: middle; margin-left: 0.5rem\">I-DES</span>\n",
       "</mark>\n",
       " 4718 san fernando rd. glendale, ca 91204 bus. \n",
       "<mark class=\"entity\" style=\"background: #ddd; padding: 0.45em 0.6em; margin: 0 0.25em; line-height: 1; border-radius: 0.35em;\">\n",
       "    818\n",
       "    <span style=\"font-size: 0.8em; font-weight: bold; line-height: 1; border-radius: 0.35em; vertical-align: middle; margin-left: 0.5rem\">B-PHONE</span>\n",
       "</mark>\n",
       " \n",
       "<mark class=\"entity\" style=\"background: #ddd; padding: 0.45em 0.6em; margin: 0 0.25em; line-height: 1; border-radius: 0.35em;\">\n",
       "    547-4220\n",
       "    <span style=\"font-size: 0.8em; font-weight: bold; line-height: 1; border-radius: 0.35em; vertical-align: middle; margin-left: 0.5rem\">I-PHONE</span>\n",
       "</mark>\n",
       " fax, 818 547-4680 \n",
       "<mark class=\"entity\" style=\"background: #ddd; padding: 0.45em 0.6em; margin: 0 0.25em; line-height: 1; border-radius: 0.35em;\">\n",
       "    info@firstprintingca.com\n",
       "    <span style=\"font-size: 0.8em; font-weight: bold; line-height: 1; border-radius: 0.35em; vertical-align: middle; margin-left: 0.5rem\">B-EMAIL</span>\n",
       "</mark>\n",
       " \n",
       "<mark class=\"entity\" style=\"background: #ddd; padding: 0.45em 0.6em; margin: 0 0.25em; line-height: 1; border-radius: 0.35em;\">\n",
       "    www.firstprintingca.com\n",
       "    <span style=\"font-size: 0.8em; font-weight: bold; line-height: 1; border-radius: 0.35em; vertical-align: middle; margin-left: 0.5rem\">B-WEB</span>\n",
       "</mark>\n",
       "</div>\n",
       "</figure>\n",
       "</body>\n",
       "</html></span>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Using the 'ent' visualizer\n",
      "Serving on http://0.0.0.0:5000 ...\n",
      "\n",
      "Shutting down server on port 5000.\n"
     ]
    }
   ],
   "source": [
    "# Get Predictions from NER Model\n",
    "doc = model_ner(content)\n",
    "\n",
    "spacy.displacy.serve(doc, style=\"ent\") # ent -> entities"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "7caa5882",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<span class=\"tex2jax_ignore\"><div class=\"entities\" style=\"line-height: 2.5; direction: ltr\">\n",
       "<mark class=\"entity\" style=\"background: #ddd; padding: 0.45em 0.6em; margin: 0 0.25em; line-height: 1; border-radius: 0.35em;\">\n",
       "    james\n",
       "    <span style=\"font-size: 0.8em; font-weight: bold; line-height: 1; border-radius: 0.35em; vertical-align: middle; margin-left: 0.5rem\">B-NAME</span>\n",
       "</mark>\n",
       " \n",
       "<mark class=\"entity\" style=\"background: #ddd; padding: 0.45em 0.6em; margin: 0 0.25em; line-height: 1; border-radius: 0.35em;\">\n",
       "    bond\n",
       "    <span style=\"font-size: 0.8em; font-weight: bold; line-height: 1; border-radius: 0.35em; vertical-align: middle; margin-left: 0.5rem\">I-NAME</span>\n",
       "</mark>\n",
       " \n",
       "<mark class=\"entity\" style=\"background: #ddd; padding: 0.45em 0.6em; margin: 0 0.25em; line-height: 1; border-radius: 0.35em;\">\n",
       "    your\n",
       "    <span style=\"font-size: 0.8em; font-weight: bold; line-height: 1; border-radius: 0.35em; vertical-align: middle; margin-left: 0.5rem\">B-ORG</span>\n",
       "</mark>\n",
       " \n",
       "<mark class=\"entity\" style=\"background: #ddd; padding: 0.45em 0.6em; margin: 0 0.25em; line-height: 1; border-radius: 0.35em;\">\n",
       "    city\n",
       "    <span style=\"font-size: 0.8em; font-weight: bold; line-height: 1; border-radius: 0.35em; vertical-align: middle; margin-left: 0.5rem\">I-ORG</span>\n",
       "</mark>\n",
       " \n",
       "<mark class=\"entity\" style=\"background: #ddd; padding: 0.45em 0.6em; margin: 0 0.25em; line-height: 1; border-radius: 0.35em;\">\n",
       "    honda\n",
       "    <span style=\"font-size: 0.8em; font-weight: bold; line-height: 1; border-radius: 0.35em; vertical-align: middle; margin-left: 0.5rem\">I-ORG</span>\n",
       "</mark>\n",
       " \n",
       "<mark class=\"entity\" style=\"background: #ddd; padding: 0.45em 0.6em; margin: 0 0.25em; line-height: 1; border-radius: 0.35em;\">\n",
       "    sales\n",
       "    <span style=\"font-size: 0.8em; font-weight: bold; line-height: 1; border-radius: 0.35em; vertical-align: middle; margin-left: 0.5rem\">B-DES</span>\n",
       "</mark>\n",
       " \n",
       "<mark class=\"entity\" style=\"background: #ddd; padding: 0.45em 0.6em; margin: 0 0.25em; line-height: 1; border-radius: 0.35em;\">\n",
       "    leasing\n",
       "    <span style=\"font-size: 0.8em; font-weight: bold; line-height: 1; border-radius: 0.35em; vertical-align: middle; margin-left: 0.5rem\">I-DES</span>\n",
       "</mark>\n",
       " \n",
       "<mark class=\"entity\" style=\"background: #ddd; padding: 0.45em 0.6em; margin: 0 0.25em; line-height: 1; border-radius: 0.35em;\">\n",
       "    consultant\n",
       "    <span style=\"font-size: 0.8em; font-weight: bold; line-height: 1; border-radius: 0.35em; vertical-align: middle; margin-left: 0.5rem\">I-DES</span>\n",
       "</mark>\n",
       " 4718 san fernando rd. glendale, ca 91204 bus. \n",
       "<mark class=\"entity\" style=\"background: #ddd; padding: 0.45em 0.6em; margin: 0 0.25em; line-height: 1; border-radius: 0.35em;\">\n",
       "    818\n",
       "    <span style=\"font-size: 0.8em; font-weight: bold; line-height: 1; border-radius: 0.35em; vertical-align: middle; margin-left: 0.5rem\">B-PHONE</span>\n",
       "</mark>\n",
       " \n",
       "<mark class=\"entity\" style=\"background: #ddd; padding: 0.45em 0.6em; margin: 0 0.25em; line-height: 1; border-radius: 0.35em;\">\n",
       "    547-4220\n",
       "    <span style=\"font-size: 0.8em; font-weight: bold; line-height: 1; border-radius: 0.35em; vertical-align: middle; margin-left: 0.5rem\">I-PHONE</span>\n",
       "</mark>\n",
       " fax, 818 547-4680 \n",
       "<mark class=\"entity\" style=\"background: #ddd; padding: 0.45em 0.6em; margin: 0 0.25em; line-height: 1; border-radius: 0.35em;\">\n",
       "    info@firstprintingca.com\n",
       "    <span style=\"font-size: 0.8em; font-weight: bold; line-height: 1; border-radius: 0.35em; vertical-align: middle; margin-left: 0.5rem\">B-EMAIL</span>\n",
       "</mark>\n",
       " \n",
       "<mark class=\"entity\" style=\"background: #ddd; padding: 0.45em 0.6em; margin: 0 0.25em; line-height: 1; border-radius: 0.35em;\">\n",
       "    www.firstprintingca.com\n",
       "    <span style=\"font-size: 0.8em; font-weight: bold; line-height: 1; border-radius: 0.35em; vertical-align: middle; margin-left: 0.5rem\">B-WEB</span>\n",
       "</mark>\n",
       "</div></span>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "spacy.displacy.render(doc, style=\"ent\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "69bbc17f",
   "metadata": {},
   "source": [
    "### Tagging"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "d3adf4f7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'text': 'james bond your city honda sales leasing consultant 4718 san fernando rd. glendale, ca 91204 bus. 818 547-4220 fax, 818 547-4680 info@firstprintingca.com www.firstprintingca.com',\n",
       " 'ents': [{'start': 0, 'end': 5, 'label': 'B-NAME'},\n",
       "  {'start': 6, 'end': 10, 'label': 'I-NAME'},\n",
       "  {'start': 11, 'end': 15, 'label': 'B-ORG'},\n",
       "  {'start': 16, 'end': 20, 'label': 'I-ORG'},\n",
       "  {'start': 21, 'end': 26, 'label': 'I-ORG'},\n",
       "  {'start': 27, 'end': 32, 'label': 'B-DES'},\n",
       "  {'start': 33, 'end': 40, 'label': 'I-DES'},\n",
       "  {'start': 41, 'end': 51, 'label': 'I-DES'},\n",
       "  {'start': 98, 'end': 101, 'label': 'B-PHONE'},\n",
       "  {'start': 102, 'end': 110, 'label': 'I-PHONE'},\n",
       "  {'start': 129, 'end': 153, 'label': 'B-EMAIL'},\n",
       "  {'start': 154, 'end': 177, 'label': 'B-WEB'}],\n",
       " 'tokens': [{'id': 0, 'start': 0, 'end': 5},\n",
       "  {'id': 1, 'start': 6, 'end': 10},\n",
       "  {'id': 2, 'start': 11, 'end': 15},\n",
       "  {'id': 3, 'start': 16, 'end': 20},\n",
       "  {'id': 4, 'start': 21, 'end': 26},\n",
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       "'james bond your city honda sales leasing consultant 4718 san fernando rd. glendale, ca 91204 bus. 818 547-4220 fax, 818 547-4680 info@firstprintingca.com www.firstprintingca.com'"
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       "'ty honda sa'"
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       "      <td>9</td>\n",
       "      <td>57</td>\n",
       "      <td>60</td>\n",
       "      <td>san</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   id  start  end       token   label\n",
       "0   0      0    5       james  B-NAME\n",
       "1   1      6   10        bond  I-NAME\n",
       "2   2     11   15        your   B-ORG\n",
       "3   3     16   20        city   I-ORG\n",
       "4   4     21   26       honda   I-ORG\n",
       "5   5     27   32       sales   B-DES\n",
       "6   6     33   40     leasing   I-DES\n",
       "7   7     41   51  consultant   I-DES\n",
       "8   8     52   56        4718     NaN\n",
       "9   9     57   60         san     NaN"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "doc_ents = pd.DataFrame(docjson[\"ents\"])[[\"start\", \"label\"]]\n",
    "dataframe_tokens = pd.merge(dataframe_tokens, doc_ents, how=\"left\", on=\"start\")\n",
    "\n",
    "dataframe_tokens.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "cc41a491",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "      <td>I-NAME</td>\n",
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       "      <td>I-ORG</td>\n",
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       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>21</td>\n",
       "      <td>26</td>\n",
       "      <td>honda</td>\n",
       "      <td>I-ORG</td>\n",
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       "      <th>7</th>\n",
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       "      <td>consultant</td>\n",
       "      <td>I-DES</td>\n",
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       "      <th>8</th>\n",
       "      <td>8</td>\n",
       "      <td>52</td>\n",
       "      <td>56</td>\n",
       "      <td>4718</td>\n",
       "      <td>O</td>\n",
       "    </tr>\n",
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       "      <th>9</th>\n",
       "      <td>9</td>\n",
       "      <td>57</td>\n",
       "      <td>60</td>\n",
       "      <td>san</td>\n",
       "      <td>O</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   id  start  end       token   label\n",
       "0   0      0    5       james  B-NAME\n",
       "1   1      6   10        bond  I-NAME\n",
       "2   2     11   15        your   B-ORG\n",
       "3   3     16   20        city   I-ORG\n",
       "4   4     21   26       honda   I-ORG\n",
       "5   5     27   32       sales   B-DES\n",
       "6   6     33   40     leasing   I-DES\n",
       "7   7     41   51  consultant   I-DES\n",
       "8   8     52   56        4718       O\n",
       "9   9     57   60         san       O"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dataframe_tokens.fillna(\"O\", inplace=True)\n",
    "\n",
    "dataframe_tokens.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "10498c8f",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <td>5</td>\n",
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      "text/plain": [
       "  level page_num block_num par_num line_num word_num left top width height  \\\n",
       "4     5        1         1       1        1        1  110  84    74     19   \n",
       "5     5        1         1       1        1        2  193  84    61     18   \n",
       "6     5        1         1       1        1        3  365  84    60     19   \n",
       "7     5        1         1       1        1        4  434  84    53     25   \n",
       "8     5        1         1       1        1        5  496  84    85     19   \n",
       "\n",
       "  conf   text  \n",
       "4   96  james  \n",
       "5   96   bond  \n",
       "6   96   your  \n",
       "7   96   city  \n",
       "8   96  honda  "
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_clean.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "da0084d0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "4      6\n",
       "5      5\n",
       "6      5\n",
       "7      5\n",
       "8      6\n",
       "10     6\n",
       "12     8\n",
       "13    11\n",
       "17     5\n",
       "18     4\n",
       "19     9\n",
       "20     4\n",
       "22    10\n",
       "23     3\n",
       "24     6\n",
       "26     5\n",
       "27     4\n",
       "28     9\n",
       "30     5\n",
       "31     4\n",
       "32     9\n",
       "34    25\n",
       "36    24\n",
       "Name: text, dtype: int64"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# join label to df_clean dataframe\n",
    "df_clean[\"text\"].apply(lambda x: len(x)+1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "ed42f874",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "4       5\n",
       "5      10\n",
       "6      15\n",
       "7      20\n",
       "8      26\n",
       "10     32\n",
       "12     40\n",
       "13     51\n",
       "17     56\n",
       "18     60\n",
       "19     69\n",
       "20     73\n",
       "22     83\n",
       "23     86\n",
       "24     92\n",
       "26     97\n",
       "27    101\n",
       "28    110\n",
       "30    115\n",
       "31    119\n",
       "32    128\n",
       "34    153\n",
       "36    177\n",
       "Name: text, dtype: int64"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# join label to df_clean dataframe\n",
    "df_clean[\"text\"].apply(lambda x: len(x)+1).cumsum() - 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "6d9496bb",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\my\\AppData\\Local\\Temp\\ipykernel_10552\\1712280030.py:1: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  df_clean[\"end\"] = df_clean[\"text\"].apply(lambda x: len(x)+1).cumsum() - 1\n",
      "C:\\Users\\my\\AppData\\Local\\Temp\\ipykernel_10552\\1712280030.py:2: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  df_clean[\"start\"] = df_clean[[\"text\", \"end\"]].apply(lambda x: x[1] - len(x[0]), axis=1)\n"
     ]
    },
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       "      <td>419</td>\n",
       "      <td>219</td>\n",
       "      <td>29</td>\n",
       "      <td>13</td>\n",
       "      <td>95</td>\n",
       "      <td>san</td>\n",
       "      <td>60</td>\n",
       "      <td>57</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   level page_num block_num par_num line_num word_num left  top width height  \\\n",
       "4      5        1         1       1        1        1  110   84    74     19   \n",
       "5      5        1         1       1        1        2  193   84    61     18   \n",
       "6      5        1         1       1        1        3  365   84    60     19   \n",
       "7      5        1         1       1        1        4  434   84    53     25   \n",
       "8      5        1         1       1        1        5  496   84    85     19   \n",
       "10     5        1         1       1        2        1   72  109    40     13   \n",
       "12     5        1         1       1        2        3  138  110    62     16   \n",
       "13     5        1         1       1        2        4  206  109    87     13   \n",
       "17     5        1         2       1        1        1  372  220    41     12   \n",
       "18     5        1         2       1        1        2  419  219    29     13   \n",
       "\n",
       "   conf        text  end  start  \n",
       "4    96       james    5      0  \n",
       "5    96        bond   10      6  \n",
       "6    96        your   15     11  \n",
       "7    96        city   20     16  \n",
       "8    96       honda   26     21  \n",
       "10   93       sales   32     27  \n",
       "12   96     leasing   40     33  \n",
       "13   96  consultant   51     41  \n",
       "17   96        4718   56     52  \n",
       "18   95         san   60     57  "
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_clean[\"end\"] = df_clean[\"text\"].apply(lambda x: len(x)+1).cumsum() - 1\n",
    "df_clean[\"start\"] = df_clean[[\"text\", \"end\"]].apply(lambda x: x[1] - len(x[0]), axis=1)\n",
    "\n",
    "df_clean.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "ca08d216",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "4       0\n",
       "5       6\n",
       "6      11\n",
       "7      16\n",
       "8      21\n",
       "10     27\n",
       "12     33\n",
       "13     41\n",
       "17     52\n",
       "18     57\n",
       "19     61\n",
       "20     70\n",
       "22     74\n",
       "23     84\n",
       "24     87\n",
       "26     93\n",
       "27     98\n",
       "28    102\n",
       "30    111\n",
       "31    116\n",
       "32    120\n",
       "34    129\n",
       "36    154\n",
       "dtype: int64"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# to get correct start position\n",
    "df_clean[[\"text\", \"end\"]].apply(lambda x: x[1] - len(x[0]), axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "9afee06b",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>0</th>\n",
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       "      <th>2</th>\n",
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       "      <td>11</td>\n",
       "      <td>your</td>\n",
       "      <td>B-ORG</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
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       "      <td>1</td>\n",
       "      <td>4</td>\n",
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       "      <td>25</td>\n",
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       "      <td>city</td>\n",
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       "      <td>city</td>\n",
       "      <td>I-ORG</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>496</td>\n",
       "      <td>84</td>\n",
       "      <td>85</td>\n",
       "      <td>19</td>\n",
       "      <td>96</td>\n",
       "      <td>honda</td>\n",
       "      <td>26</td>\n",
       "      <td>21</td>\n",
       "      <td>honda</td>\n",
       "      <td>I-ORG</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
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       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>72</td>\n",
       "      <td>109</td>\n",
       "      <td>40</td>\n",
       "      <td>13</td>\n",
       "      <td>93</td>\n",
       "      <td>sales</td>\n",
       "      <td>32</td>\n",
       "      <td>27</td>\n",
       "      <td>sales</td>\n",
       "      <td>B-DES</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>138</td>\n",
       "      <td>110</td>\n",
       "      <td>62</td>\n",
       "      <td>16</td>\n",
       "      <td>96</td>\n",
       "      <td>leasing</td>\n",
       "      <td>40</td>\n",
       "      <td>33</td>\n",
       "      <td>leasing</td>\n",
       "      <td>I-DES</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "      <td>206</td>\n",
       "      <td>109</td>\n",
       "      <td>87</td>\n",
       "      <td>13</td>\n",
       "      <td>96</td>\n",
       "      <td>consultant</td>\n",
       "      <td>51</td>\n",
       "      <td>41</td>\n",
       "      <td>consultant</td>\n",
       "      <td>I-DES</td>\n",
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       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
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       "      <td>220</td>\n",
       "      <td>41</td>\n",
       "      <td>12</td>\n",
       "      <td>96</td>\n",
       "      <td>4718</td>\n",
       "      <td>56</td>\n",
       "      <td>52</td>\n",
       "      <td>4718</td>\n",
       "      <td>O</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>419</td>\n",
       "      <td>219</td>\n",
       "      <td>29</td>\n",
       "      <td>13</td>\n",
       "      <td>95</td>\n",
       "      <td>san</td>\n",
       "      <td>60</td>\n",
       "      <td>57</td>\n",
       "      <td>san</td>\n",
       "      <td>O</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  level page_num block_num par_num line_num word_num left  top width height  \\\n",
       "0     5        1         1       1        1        1  110   84    74     19   \n",
       "1     5        1         1       1        1        2  193   84    61     18   \n",
       "2     5        1         1       1        1        3  365   84    60     19   \n",
       "3     5        1         1       1        1        4  434   84    53     25   \n",
       "4     5        1         1       1        1        5  496   84    85     19   \n",
       "5     5        1         1       1        2        1   72  109    40     13   \n",
       "6     5        1         1       1        2        3  138  110    62     16   \n",
       "7     5        1         1       1        2        4  206  109    87     13   \n",
       "8     5        1         2       1        1        1  372  220    41     12   \n",
       "9     5        1         2       1        1        2  419  219    29     13   \n",
       "\n",
       "  conf        text  end  start       token   label  \n",
       "0   96       james    5      0       james  B-NAME  \n",
       "1   96        bond   10      6        bond  I-NAME  \n",
       "2   96        your   15     11        your   B-ORG  \n",
       "3   96        city   20     16        city   I-ORG  \n",
       "4   96       honda   26     21       honda   I-ORG  \n",
       "5   93       sales   32     27       sales   B-DES  \n",
       "6   96     leasing   40     33     leasing   I-DES  \n",
       "7   96  consultant   51     41  consultant   I-DES  \n",
       "8   96        4718   56     52        4718       O  \n",
       "9   95         san   60     57         san       O  "
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# inner join with start \n",
    "\n",
    "dataframe_info = pd.merge(df_clean, dataframe_tokens[[\"start\", \"token\", \"label\"]], how=\"inner\", on=\"start\")\n",
    "dataframe_info.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "b01be36d",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
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       "      <td>O</td>\n",
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       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
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       "      <td>50</td>\n",
       "      <td>13</td>\n",
       "      <td>94</td>\n",
       "      <td>91204</td>\n",
       "      <td>92</td>\n",
       "      <td>87</td>\n",
       "      <td>91204</td>\n",
       "      <td>O</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>371</td>\n",
       "      <td>264</td>\n",
       "      <td>34</td>\n",
       "      <td>13</td>\n",
       "      <td>96</td>\n",
       "      <td>bus.</td>\n",
       "      <td>97</td>\n",
       "      <td>93</td>\n",
       "      <td>bus</td>\n",
       "      <td>O</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>413</td>\n",
       "      <td>264</td>\n",
       "      <td>41</td>\n",
       "      <td>15</td>\n",
       "      <td>96</td>\n",
       "      <td>818</td>\n",
       "      <td>101</td>\n",
       "      <td>98</td>\n",
       "      <td>818</td>\n",
       "      <td>B-PHONE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>460</td>\n",
       "      <td>264</td>\n",
       "      <td>80</td>\n",
       "      <td>13</td>\n",
       "      <td>96</td>\n",
       "      <td>547-4220</td>\n",
       "      <td>110</td>\n",
       "      <td>102</td>\n",
       "      <td>547</td>\n",
       "      <td>I-PHONE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>372</td>\n",
       "      <td>287</td>\n",
       "      <td>31</td>\n",
       "      <td>13</td>\n",
       "      <td>96</td>\n",
       "      <td>fax,</td>\n",
       "      <td>115</td>\n",
       "      <td>111</td>\n",
       "      <td>fax</td>\n",
       "      <td>O</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "      <td>410</td>\n",
       "      <td>287</td>\n",
       "      <td>41</td>\n",
       "      <td>15</td>\n",
       "      <td>96</td>\n",
       "      <td>818</td>\n",
       "      <td>119</td>\n",
       "      <td>116</td>\n",
       "      <td>818</td>\n",
       "      <td>O</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>3</td>\n",
       "      <td>458</td>\n",
       "      <td>287</td>\n",
       "      <td>80</td>\n",
       "      <td>13</td>\n",
       "      <td>96</td>\n",
       "      <td>547-4680</td>\n",
       "      <td>128</td>\n",
       "      <td>120</td>\n",
       "      <td>547</td>\n",
       "      <td>O</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>372</td>\n",
       "      <td>308</td>\n",
       "      <td>213</td>\n",
       "      <td>18</td>\n",
       "      <td>84</td>\n",
       "      <td>info@firstprintingca.com</td>\n",
       "      <td>153</td>\n",
       "      <td>129</td>\n",
       "      <td>info@firstprintingca.com</td>\n",
       "      <td>B-EMAIL</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "      <td>371</td>\n",
       "      <td>332</td>\n",
       "      <td>211</td>\n",
       "      <td>16</td>\n",
       "      <td>63</td>\n",
       "      <td>www.firstprintingca.com</td>\n",
       "      <td>177</td>\n",
       "      <td>154</td>\n",
       "      <td>www.firstprintingca.com</td>\n",
       "      <td>B-WEB</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   level page_num block_num par_num line_num word_num left  top width height  \\\n",
       "13     5        1         2       1        2        2  454  242    24     13   \n",
       "14     5        1         2       1        2        3  484  242    50     13   \n",
       "15     5        1         2       1        3        1  371  264    34     13   \n",
       "16     5        1         2       1        3        2  413  264    41     15   \n",
       "17     5        1         2       1        3        3  460  264    80     13   \n",
       "18     5        1         2       1        4        1  372  287    31     13   \n",
       "19     5        1         2       1        4        2  410  287    41     15   \n",
       "20     5        1         2       1        4        3  458  287    80     13   \n",
       "21     5        1         2       1        5        1  372  308   213     18   \n",
       "22     5        1         2       1        6        1  371  332   211     16   \n",
       "\n",
       "   conf                      text  end  start                     token  \\\n",
       "13   94                        ca   86     84                        ca   \n",
       "14   94                     91204   92     87                     91204   \n",
       "15   96                      bus.   97     93                       bus   \n",
       "16   96                       818  101     98                       818   \n",
       "17   96                  547-4220  110    102                       547   \n",
       "18   96                      fax,  115    111                       fax   \n",
       "19   96                       818  119    116                       818   \n",
       "20   96                  547-4680  128    120                       547   \n",
       "21   84  info@firstprintingca.com  153    129  info@firstprintingca.com   \n",
       "22   63   www.firstprintingca.com  177    154   www.firstprintingca.com   \n",
       "\n",
       "      label  \n",
       "13        O  \n",
       "14        O  \n",
       "15        O  \n",
       "16  B-PHONE  \n",
       "17  I-PHONE  \n",
       "18        O  \n",
       "19        O  \n",
       "20        O  \n",
       "21  B-EMAIL  \n",
       "22    B-WEB  "
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dataframe_info.tail(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "8db916df",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>level</th>\n",
       "      <th>page_num</th>\n",
       "      <th>block_num</th>\n",
       "      <th>par_num</th>\n",
       "      <th>line_num</th>\n",
       "      <th>word_num</th>\n",
       "      <th>left</th>\n",
       "      <th>top</th>\n",
       "      <th>width</th>\n",
       "      <th>height</th>\n",
       "      <th>conf</th>\n",
       "      <th>text</th>\n",
       "      <th>end</th>\n",
       "      <th>start</th>\n",
       "      <th>token</th>\n",
       "      <th>label</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>110</td>\n",
       "      <td>84</td>\n",
       "      <td>74</td>\n",
       "      <td>19</td>\n",
       "      <td>96</td>\n",
       "      <td>james</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>james</td>\n",
       "      <td>B-NAME</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>193</td>\n",
       "      <td>84</td>\n",
       "      <td>61</td>\n",
       "      <td>18</td>\n",
       "      <td>96</td>\n",
       "      <td>bond</td>\n",
       "      <td>10</td>\n",
       "      <td>6</td>\n",
       "      <td>bond</td>\n",
       "      <td>I-NAME</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>365</td>\n",
       "      <td>84</td>\n",
       "      <td>60</td>\n",
       "      <td>19</td>\n",
       "      <td>96</td>\n",
       "      <td>your</td>\n",
       "      <td>15</td>\n",
       "      <td>11</td>\n",
       "      <td>your</td>\n",
       "      <td>B-ORG</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>434</td>\n",
       "      <td>84</td>\n",
       "      <td>53</td>\n",
       "      <td>25</td>\n",
       "      <td>96</td>\n",
       "      <td>city</td>\n",
       "      <td>20</td>\n",
       "      <td>16</td>\n",
       "      <td>city</td>\n",
       "      <td>I-ORG</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>496</td>\n",
       "      <td>84</td>\n",
       "      <td>85</td>\n",
       "      <td>19</td>\n",
       "      <td>96</td>\n",
       "      <td>honda</td>\n",
       "      <td>26</td>\n",
       "      <td>21</td>\n",
       "      <td>honda</td>\n",
       "      <td>I-ORG</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>72</td>\n",
       "      <td>109</td>\n",
       "      <td>40</td>\n",
       "      <td>13</td>\n",
       "      <td>93</td>\n",
       "      <td>sales</td>\n",
       "      <td>32</td>\n",
       "      <td>27</td>\n",
       "      <td>sales</td>\n",
       "      <td>B-DES</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>138</td>\n",
       "      <td>110</td>\n",
       "      <td>62</td>\n",
       "      <td>16</td>\n",
       "      <td>96</td>\n",
       "      <td>leasing</td>\n",
       "      <td>40</td>\n",
       "      <td>33</td>\n",
       "      <td>leasing</td>\n",
       "      <td>I-DES</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "      <td>206</td>\n",
       "      <td>109</td>\n",
       "      <td>87</td>\n",
       "      <td>13</td>\n",
       "      <td>96</td>\n",
       "      <td>consultant</td>\n",
       "      <td>51</td>\n",
       "      <td>41</td>\n",
       "      <td>consultant</td>\n",
       "      <td>I-DES</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>413</td>\n",
       "      <td>264</td>\n",
       "      <td>41</td>\n",
       "      <td>15</td>\n",
       "      <td>96</td>\n",
       "      <td>818</td>\n",
       "      <td>101</td>\n",
       "      <td>98</td>\n",
       "      <td>818</td>\n",
       "      <td>B-PHONE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>460</td>\n",
       "      <td>264</td>\n",
       "      <td>80</td>\n",
       "      <td>13</td>\n",
       "      <td>96</td>\n",
       "      <td>547-4220</td>\n",
       "      <td>110</td>\n",
       "      <td>102</td>\n",
       "      <td>547</td>\n",
       "      <td>I-PHONE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>372</td>\n",
       "      <td>308</td>\n",
       "      <td>213</td>\n",
       "      <td>18</td>\n",
       "      <td>84</td>\n",
       "      <td>info@firstprintingca.com</td>\n",
       "      <td>153</td>\n",
       "      <td>129</td>\n",
       "      <td>info@firstprintingca.com</td>\n",
       "      <td>B-EMAIL</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "      <td>371</td>\n",
       "      <td>332</td>\n",
       "      <td>211</td>\n",
       "      <td>16</td>\n",
       "      <td>63</td>\n",
       "      <td>www.firstprintingca.com</td>\n",
       "      <td>177</td>\n",
       "      <td>154</td>\n",
       "      <td>www.firstprintingca.com</td>\n",
       "      <td>B-WEB</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   level page_num block_num par_num line_num word_num left  top width height  \\\n",
       "0      5        1         1       1        1        1  110   84    74     19   \n",
       "1      5        1         1       1        1        2  193   84    61     18   \n",
       "2      5        1         1       1        1        3  365   84    60     19   \n",
       "3      5        1         1       1        1        4  434   84    53     25   \n",
       "4      5        1         1       1        1        5  496   84    85     19   \n",
       "5      5        1         1       1        2        1   72  109    40     13   \n",
       "6      5        1         1       1        2        3  138  110    62     16   \n",
       "7      5        1         1       1        2        4  206  109    87     13   \n",
       "16     5        1         2       1        3        2  413  264    41     15   \n",
       "17     5        1         2       1        3        3  460  264    80     13   \n",
       "21     5        1         2       1        5        1  372  308   213     18   \n",
       "22     5        1         2       1        6        1  371  332   211     16   \n",
       "\n",
       "   conf                      text  end  start                     token  \\\n",
       "0    96                     james    5      0                     james   \n",
       "1    96                      bond   10      6                      bond   \n",
       "2    96                      your   15     11                      your   \n",
       "3    96                      city   20     16                      city   \n",
       "4    96                     honda   26     21                     honda   \n",
       "5    93                     sales   32     27                     sales   \n",
       "6    96                   leasing   40     33                   leasing   \n",
       "7    96                consultant   51     41                consultant   \n",
       "16   96                       818  101     98                       818   \n",
       "17   96                  547-4220  110    102                       547   \n",
       "21   84  info@firstprintingca.com  153    129  info@firstprintingca.com   \n",
       "22   63   www.firstprintingca.com  177    154   www.firstprintingca.com   \n",
       "\n",
       "      label  \n",
       "0    B-NAME  \n",
       "1    I-NAME  \n",
       "2     B-ORG  \n",
       "3     I-ORG  \n",
       "4     I-ORG  \n",
       "5     B-DES  \n",
       "6     I-DES  \n",
       "7     I-DES  \n",
       "16  B-PHONE  \n",
       "17  I-PHONE  \n",
       "21  B-EMAIL  \n",
       "22    B-WEB  "
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bb_df = dataframe_info.query(\"label != 'O' \")\n",
    "\n",
    "bb_df"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1b43f236",
   "metadata": {},
   "source": [
    "### Bounding Box"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "7d784390",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(-0.5, 706.5, 436.5, -0.5)"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "img = image.copy()\n",
    "\n",
    "for x,y,w,h,label in bb_df[[\"left\",\"top\",\"width\",\"height\",\"label\"]].values:\n",
    "    x = int(x)\n",
    "    y = int(y)\n",
    "    w = int(w)\n",
    "    h = int(h)\n",
    "    \n",
    "    cv2.rectangle(img, (x,y), (x+w, y+h), (0,255,0), 2)\n",
    "    cv2.putText(img, str(label), (x,y), cv2.FONT_HERSHEY_PLAIN, 1, (255,0,0), 2)\n",
    "    \n",
    "plt.imshow(img)\n",
    "plt.axis(\"off\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "a628254a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>level</th>\n",
       "      <th>page_num</th>\n",
       "      <th>block_num</th>\n",
       "      <th>par_num</th>\n",
       "      <th>line_num</th>\n",
       "      <th>word_num</th>\n",
       "      <th>left</th>\n",
       "      <th>top</th>\n",
       "      <th>width</th>\n",
       "      <th>height</th>\n",
       "      <th>conf</th>\n",
       "      <th>text</th>\n",
       "      <th>end</th>\n",
       "      <th>start</th>\n",
       "      <th>token</th>\n",
       "      <th>label</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>110</td>\n",
       "      <td>84</td>\n",
       "      <td>74</td>\n",
       "      <td>19</td>\n",
       "      <td>96</td>\n",
       "      <td>james</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>james</td>\n",
       "      <td>B-NAME</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>193</td>\n",
       "      <td>84</td>\n",
       "      <td>61</td>\n",
       "      <td>18</td>\n",
       "      <td>96</td>\n",
       "      <td>bond</td>\n",
       "      <td>10</td>\n",
       "      <td>6</td>\n",
       "      <td>bond</td>\n",
       "      <td>I-NAME</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>365</td>\n",
       "      <td>84</td>\n",
       "      <td>60</td>\n",
       "      <td>19</td>\n",
       "      <td>96</td>\n",
       "      <td>your</td>\n",
       "      <td>15</td>\n",
       "      <td>11</td>\n",
       "      <td>your</td>\n",
       "      <td>B-ORG</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>434</td>\n",
       "      <td>84</td>\n",
       "      <td>53</td>\n",
       "      <td>25</td>\n",
       "      <td>96</td>\n",
       "      <td>city</td>\n",
       "      <td>20</td>\n",
       "      <td>16</td>\n",
       "      <td>city</td>\n",
       "      <td>I-ORG</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>496</td>\n",
       "      <td>84</td>\n",
       "      <td>85</td>\n",
       "      <td>19</td>\n",
       "      <td>96</td>\n",
       "      <td>honda</td>\n",
       "      <td>26</td>\n",
       "      <td>21</td>\n",
       "      <td>honda</td>\n",
       "      <td>I-ORG</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>72</td>\n",
       "      <td>109</td>\n",
       "      <td>40</td>\n",
       "      <td>13</td>\n",
       "      <td>93</td>\n",
       "      <td>sales</td>\n",
       "      <td>32</td>\n",
       "      <td>27</td>\n",
       "      <td>sales</td>\n",
       "      <td>B-DES</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>138</td>\n",
       "      <td>110</td>\n",
       "      <td>62</td>\n",
       "      <td>16</td>\n",
       "      <td>96</td>\n",
       "      <td>leasing</td>\n",
       "      <td>40</td>\n",
       "      <td>33</td>\n",
       "      <td>leasing</td>\n",
       "      <td>I-DES</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "      <td>206</td>\n",
       "      <td>109</td>\n",
       "      <td>87</td>\n",
       "      <td>13</td>\n",
       "      <td>96</td>\n",
       "      <td>consultant</td>\n",
       "      <td>51</td>\n",
       "      <td>41</td>\n",
       "      <td>consultant</td>\n",
       "      <td>I-DES</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>413</td>\n",
       "      <td>264</td>\n",
       "      <td>41</td>\n",
       "      <td>15</td>\n",
       "      <td>96</td>\n",
       "      <td>818</td>\n",
       "      <td>101</td>\n",
       "      <td>98</td>\n",
       "      <td>818</td>\n",
       "      <td>B-PHONE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>460</td>\n",
       "      <td>264</td>\n",
       "      <td>80</td>\n",
       "      <td>13</td>\n",
       "      <td>96</td>\n",
       "      <td>547-4220</td>\n",
       "      <td>110</td>\n",
       "      <td>102</td>\n",
       "      <td>547</td>\n",
       "      <td>I-PHONE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
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       "      <td>info@firstprintingca.com</td>\n",
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       "0      5        1         1       1        1        1  110   84    74     19   \n",
       "1      5        1         1       1        1        2  193   84    61     18   \n",
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       "22     5        1         2       1        6        1  371  332   211     16   \n",
       "\n",
       "   conf                      text  end  start                     token  \\\n",
       "0    96                     james    5      0                     james   \n",
       "1    96                      bond   10      6                      bond   \n",
       "2    96                      your   15     11                      your   \n",
       "3    96                      city   20     16                      city   \n",
       "4    96                     honda   26     21                     honda   \n",
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       "6    96                   leasing   40     33                   leasing   \n",
       "7    96                consultant   51     41                consultant   \n",
       "16   96                       818  101     98                       818   \n",
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       "21   84  info@firstprintingca.com  153    129  info@firstprintingca.com   \n",
       "22   63   www.firstprintingca.com  177    154   www.firstprintingca.com   \n",
       "\n",
       "      label  \n",
       "0    B-NAME  \n",
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     },
     "execution_count": 29,
     "metadata": {},
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   "source": [
    "bb_df"
   ]
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   "cell_type": "code",
   "execution_count": 30,
   "id": "246e2760",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\my\\AppData\\Local\\Temp\\ipykernel_10552\\284535532.py:1: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  bb_df[\"label\"] = bb_df[\"label\"].apply(lambda x: x[2:])\n"
     ]
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       "22     5        1         2       1        6        1  371  332   211     16   \n",
       "\n",
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     },
     "execution_count": 30,
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    }
   ],
   "source": [
    "bb_df[\"label\"] = bb_df[\"label\"].apply(lambda x: x[2:])\n",
    "bb_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "8a30d53f",
   "metadata": {},
   "outputs": [],
   "source": [
    "# group the label\n",
    "class groupgen():\n",
    "    def __init__(self):\n",
    "        self.id = 0\n",
    "        self.text = \"\"\n",
    "        \n",
    "    def getgroup(self, text):\n",
    "        if self.text == text:\n",
    "            return self.id\n",
    "        else:\n",
    "            self.id += 1\n",
    "            self.text = text\n",
    "            return self.id\n",
    "        \n",
    "grp_gen = groupgen()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "a2895923",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\my\\AppData\\Local\\Temp\\ipykernel_10552\\119033978.py:1: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  bb_df[\"group\"] = bb_df[\"label\"].apply(grp_gen.getgroup)\n"
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       "      <td>25</td>\n",
       "      <td>96</td>\n",
       "      <td>city</td>\n",
       "      <td>20</td>\n",
       "      <td>16</td>\n",
       "      <td>city</td>\n",
       "      <td>ORG</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>496</td>\n",
       "      <td>84</td>\n",
       "      <td>85</td>\n",
       "      <td>19</td>\n",
       "      <td>96</td>\n",
       "      <td>honda</td>\n",
       "      <td>26</td>\n",
       "      <td>21</td>\n",
       "      <td>honda</td>\n",
       "      <td>ORG</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>72</td>\n",
       "      <td>109</td>\n",
       "      <td>40</td>\n",
       "      <td>13</td>\n",
       "      <td>93</td>\n",
       "      <td>sales</td>\n",
       "      <td>32</td>\n",
       "      <td>27</td>\n",
       "      <td>sales</td>\n",
       "      <td>DES</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>138</td>\n",
       "      <td>110</td>\n",
       "      <td>62</td>\n",
       "      <td>16</td>\n",
       "      <td>96</td>\n",
       "      <td>leasing</td>\n",
       "      <td>40</td>\n",
       "      <td>33</td>\n",
       "      <td>leasing</td>\n",
       "      <td>DES</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "      <td>206</td>\n",
       "      <td>109</td>\n",
       "      <td>87</td>\n",
       "      <td>13</td>\n",
       "      <td>96</td>\n",
       "      <td>consultant</td>\n",
       "      <td>51</td>\n",
       "      <td>41</td>\n",
       "      <td>consultant</td>\n",
       "      <td>DES</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>413</td>\n",
       "      <td>264</td>\n",
       "      <td>41</td>\n",
       "      <td>15</td>\n",
       "      <td>96</td>\n",
       "      <td>818</td>\n",
       "      <td>101</td>\n",
       "      <td>98</td>\n",
       "      <td>818</td>\n",
       "      <td>PHONE</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>460</td>\n",
       "      <td>264</td>\n",
       "      <td>80</td>\n",
       "      <td>13</td>\n",
       "      <td>96</td>\n",
       "      <td>547-4220</td>\n",
       "      <td>110</td>\n",
       "      <td>102</td>\n",
       "      <td>547</td>\n",
       "      <td>PHONE</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>372</td>\n",
       "      <td>308</td>\n",
       "      <td>213</td>\n",
       "      <td>18</td>\n",
       "      <td>84</td>\n",
       "      <td>info@firstprintingca.com</td>\n",
       "      <td>153</td>\n",
       "      <td>129</td>\n",
       "      <td>info@firstprintingca.com</td>\n",
       "      <td>EMAIL</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "      <td>371</td>\n",
       "      <td>332</td>\n",
       "      <td>211</td>\n",
       "      <td>16</td>\n",
       "      <td>63</td>\n",
       "      <td>www.firstprintingca.com</td>\n",
       "      <td>177</td>\n",
       "      <td>154</td>\n",
       "      <td>www.firstprintingca.com</td>\n",
       "      <td>WEB</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   level page_num block_num par_num line_num word_num left  top width height  \\\n",
       "0      5        1         1       1        1        1  110   84    74     19   \n",
       "1      5        1         1       1        1        2  193   84    61     18   \n",
       "2      5        1         1       1        1        3  365   84    60     19   \n",
       "3      5        1         1       1        1        4  434   84    53     25   \n",
       "4      5        1         1       1        1        5  496   84    85     19   \n",
       "5      5        1         1       1        2        1   72  109    40     13   \n",
       "6      5        1         1       1        2        3  138  110    62     16   \n",
       "7      5        1         1       1        2        4  206  109    87     13   \n",
       "16     5        1         2       1        3        2  413  264    41     15   \n",
       "17     5        1         2       1        3        3  460  264    80     13   \n",
       "21     5        1         2       1        5        1  372  308   213     18   \n",
       "22     5        1         2       1        6        1  371  332   211     16   \n",
       "\n",
       "   conf                      text  end  start                     token  \\\n",
       "0    96                     james    5      0                     james   \n",
       "1    96                      bond   10      6                      bond   \n",
       "2    96                      your   15     11                      your   \n",
       "3    96                      city   20     16                      city   \n",
       "4    96                     honda   26     21                     honda   \n",
       "5    93                     sales   32     27                     sales   \n",
       "6    96                   leasing   40     33                   leasing   \n",
       "7    96                consultant   51     41                consultant   \n",
       "16   96                       818  101     98                       818   \n",
       "17   96                  547-4220  110    102                       547   \n",
       "21   84  info@firstprintingca.com  153    129  info@firstprintingca.com   \n",
       "22   63   www.firstprintingca.com  177    154   www.firstprintingca.com   \n",
       "\n",
       "    label  group  \n",
       "0    NAME      1  \n",
       "1    NAME      1  \n",
       "2     ORG      2  \n",
       "3     ORG      2  \n",
       "4     ORG      2  \n",
       "5     DES      3  \n",
       "6     DES      3  \n",
       "7     DES      3  \n",
       "16  PHONE      4  \n",
       "17  PHONE      4  \n",
       "21  EMAIL      5  \n",
       "22    WEB      6  "
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bb_df[\"group\"] = bb_df[\"label\"].apply(grp_gen.getgroup)\n",
    "bb_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "f33dd8e1",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\my\\AppData\\Local\\Temp\\ipykernel_10552\\2713810823.py:3: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  bb_df[[\"left\",\"top\",\"width\",\"height\"]] = bb_df[[\"left\",\"top\",\"width\",\"height\"]].astype(int)\n",
      "C:\\Users\\my\\AppData\\Local\\Temp\\ipykernel_10552\\2713810823.py:5: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  bb_df[\"right\"] = bb_df[\"left\"] + bb_df[\"width\"]\n",
      "C:\\Users\\my\\AppData\\Local\\Temp\\ipykernel_10552\\2713810823.py:6: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  bb_df[\"bottom\"] = bb_df[\"top\"] + bb_df[\"height\"]\n"
     ]
    }
   ],
   "source": [
    "# right and bottom of bounding box\n",
    "\n",
    "bb_df[[\"left\",\"top\",\"width\",\"height\"]] = bb_df[[\"left\",\"top\",\"width\",\"height\"]].astype(int)\n",
    "\n",
    "bb_df[\"right\"] = bb_df[\"left\"] + bb_df[\"width\"]\n",
    "bb_df[\"bottom\"] = bb_df[\"top\"] + bb_df[\"height\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "63509083",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <td>NAME</td>\n",
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       "      <td>1</td>\n",
       "      <td>1</td>\n",
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       "      <td>61</td>\n",
       "      <td>18</td>\n",
       "      <td>96</td>\n",
       "      <td>bond</td>\n",
       "      <td>10</td>\n",
       "      <td>6</td>\n",
       "      <td>bond</td>\n",
       "      <td>NAME</td>\n",
       "      <td>1</td>\n",
       "      <td>254</td>\n",
       "      <td>102</td>\n",
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       "      <td>84</td>\n",
       "      <td>60</td>\n",
       "      <td>19</td>\n",
       "      <td>96</td>\n",
       "      <td>your</td>\n",
       "      <td>15</td>\n",
       "      <td>11</td>\n",
       "      <td>your</td>\n",
       "      <td>ORG</td>\n",
       "      <td>2</td>\n",
       "      <td>425</td>\n",
       "      <td>103</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>434</td>\n",
       "      <td>84</td>\n",
       "      <td>53</td>\n",
       "      <td>25</td>\n",
       "      <td>96</td>\n",
       "      <td>city</td>\n",
       "      <td>20</td>\n",
       "      <td>16</td>\n",
       "      <td>city</td>\n",
       "      <td>ORG</td>\n",
       "      <td>2</td>\n",
       "      <td>487</td>\n",
       "      <td>109</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>496</td>\n",
       "      <td>84</td>\n",
       "      <td>85</td>\n",
       "      <td>19</td>\n",
       "      <td>96</td>\n",
       "      <td>honda</td>\n",
       "      <td>26</td>\n",
       "      <td>21</td>\n",
       "      <td>honda</td>\n",
       "      <td>ORG</td>\n",
       "      <td>2</td>\n",
       "      <td>581</td>\n",
       "      <td>103</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>72</td>\n",
       "      <td>109</td>\n",
       "      <td>40</td>\n",
       "      <td>13</td>\n",
       "      <td>93</td>\n",
       "      <td>sales</td>\n",
       "      <td>32</td>\n",
       "      <td>27</td>\n",
       "      <td>sales</td>\n",
       "      <td>DES</td>\n",
       "      <td>3</td>\n",
       "      <td>112</td>\n",
       "      <td>122</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>138</td>\n",
       "      <td>110</td>\n",
       "      <td>62</td>\n",
       "      <td>16</td>\n",
       "      <td>96</td>\n",
       "      <td>leasing</td>\n",
       "      <td>40</td>\n",
       "      <td>33</td>\n",
       "      <td>leasing</td>\n",
       "      <td>DES</td>\n",
       "      <td>3</td>\n",
       "      <td>200</td>\n",
       "      <td>126</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "      <td>206</td>\n",
       "      <td>109</td>\n",
       "      <td>87</td>\n",
       "      <td>13</td>\n",
       "      <td>96</td>\n",
       "      <td>consultant</td>\n",
       "      <td>51</td>\n",
       "      <td>41</td>\n",
       "      <td>consultant</td>\n",
       "      <td>DES</td>\n",
       "      <td>3</td>\n",
       "      <td>293</td>\n",
       "      <td>122</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>413</td>\n",
       "      <td>264</td>\n",
       "      <td>41</td>\n",
       "      <td>15</td>\n",
       "      <td>96</td>\n",
       "      <td>818</td>\n",
       "      <td>101</td>\n",
       "      <td>98</td>\n",
       "      <td>818</td>\n",
       "      <td>PHONE</td>\n",
       "      <td>4</td>\n",
       "      <td>454</td>\n",
       "      <td>279</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>460</td>\n",
       "      <td>264</td>\n",
       "      <td>80</td>\n",
       "      <td>13</td>\n",
       "      <td>96</td>\n",
       "      <td>547-4220</td>\n",
       "      <td>110</td>\n",
       "      <td>102</td>\n",
       "      <td>547</td>\n",
       "      <td>PHONE</td>\n",
       "      <td>4</td>\n",
       "      <td>540</td>\n",
       "      <td>277</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>372</td>\n",
       "      <td>308</td>\n",
       "      <td>213</td>\n",
       "      <td>18</td>\n",
       "      <td>84</td>\n",
       "      <td>info@firstprintingca.com</td>\n",
       "      <td>153</td>\n",
       "      <td>129</td>\n",
       "      <td>info@firstprintingca.com</td>\n",
       "      <td>EMAIL</td>\n",
       "      <td>5</td>\n",
       "      <td>585</td>\n",
       "      <td>326</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "      <td>371</td>\n",
       "      <td>332</td>\n",
       "      <td>211</td>\n",
       "      <td>16</td>\n",
       "      <td>63</td>\n",
       "      <td>www.firstprintingca.com</td>\n",
       "      <td>177</td>\n",
       "      <td>154</td>\n",
       "      <td>www.firstprintingca.com</td>\n",
       "      <td>WEB</td>\n",
       "      <td>6</td>\n",
       "      <td>582</td>\n",
       "      <td>348</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   level page_num block_num par_num line_num word_num  left  top  width  \\\n",
       "0      5        1         1       1        1        1   110   84     74   \n",
       "1      5        1         1       1        1        2   193   84     61   \n",
       "2      5        1         1       1        1        3   365   84     60   \n",
       "3      5        1         1       1        1        4   434   84     53   \n",
       "4      5        1         1       1        1        5   496   84     85   \n",
       "5      5        1         1       1        2        1    72  109     40   \n",
       "6      5        1         1       1        2        3   138  110     62   \n",
       "7      5        1         1       1        2        4   206  109     87   \n",
       "16     5        1         2       1        3        2   413  264     41   \n",
       "17     5        1         2       1        3        3   460  264     80   \n",
       "21     5        1         2       1        5        1   372  308    213   \n",
       "22     5        1         2       1        6        1   371  332    211   \n",
       "\n",
       "    height conf                      text  end  start  \\\n",
       "0       19   96                     james    5      0   \n",
       "1       18   96                      bond   10      6   \n",
       "2       19   96                      your   15     11   \n",
       "3       25   96                      city   20     16   \n",
       "4       19   96                     honda   26     21   \n",
       "5       13   93                     sales   32     27   \n",
       "6       16   96                   leasing   40     33   \n",
       "7       13   96                consultant   51     41   \n",
       "16      15   96                       818  101     98   \n",
       "17      13   96                  547-4220  110    102   \n",
       "21      18   84  info@firstprintingca.com  153    129   \n",
       "22      16   63   www.firstprintingca.com  177    154   \n",
       "\n",
       "                       token  label  group  right  bottom  \n",
       "0                      james   NAME      1    184     103  \n",
       "1                       bond   NAME      1    254     102  \n",
       "2                       your    ORG      2    425     103  \n",
       "3                       city    ORG      2    487     109  \n",
       "4                      honda    ORG      2    581     103  \n",
       "5                      sales    DES      3    112     122  \n",
       "6                    leasing    DES      3    200     126  \n",
       "7                 consultant    DES      3    293     122  \n",
       "16                       818  PHONE      4    454     279  \n",
       "17                       547  PHONE      4    540     277  \n",
       "21  info@firstprintingca.com  EMAIL      5    585     326  \n",
       "22   www.firstprintingca.com    WEB      6    582     348  "
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bb_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "2123536c",
   "metadata": {},
   "outputs": [],
   "source": [
    "# tagging: groupby by group\n",
    "\n",
    "col_group = [\"left\",\"top\",\"right\",\"bottom\",\"label\",\"token\",\"group\"]\n",
    "\n",
    "group_tag_img = bb_df[col_group].groupby(by=\"group\")\n",
    "\n",
    "img_tagging = group_tag_img.agg({\n",
    "    \n",
    "    \"left\": min,\n",
    "    \"right\": max,\n",
    "    \"top\": min,\n",
    "    \"bottom\": max,\n",
    "    \"label\": np.unique,\n",
    "    \"token\": lambda x: \" \".join(x)\n",
    "    \n",
    "})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "8dd42a59",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>left</th>\n",
       "      <th>right</th>\n",
       "      <th>top</th>\n",
       "      <th>bottom</th>\n",
       "      <th>label</th>\n",
       "      <th>token</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>group</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>110</td>\n",
       "      <td>254</td>\n",
       "      <td>84</td>\n",
       "      <td>103</td>\n",
       "      <td>[NAME]</td>\n",
       "      <td>james bond</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>365</td>\n",
       "      <td>581</td>\n",
       "      <td>84</td>\n",
       "      <td>109</td>\n",
       "      <td>[ORG]</td>\n",
       "      <td>your city honda</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>72</td>\n",
       "      <td>293</td>\n",
       "      <td>109</td>\n",
       "      <td>126</td>\n",
       "      <td>[DES]</td>\n",
       "      <td>sales leasing consultant</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>413</td>\n",
       "      <td>540</td>\n",
       "      <td>264</td>\n",
       "      <td>279</td>\n",
       "      <td>[PHONE]</td>\n",
       "      <td>818 547</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>372</td>\n",
       "      <td>585</td>\n",
       "      <td>308</td>\n",
       "      <td>326</td>\n",
       "      <td>[EMAIL]</td>\n",
       "      <td>info@firstprintingca.com</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>371</td>\n",
       "      <td>582</td>\n",
       "      <td>332</td>\n",
       "      <td>348</td>\n",
       "      <td>[WEB]</td>\n",
       "      <td>www.firstprintingca.com</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       left  right  top  bottom    label                     token\n",
       "group                                                             \n",
       "1       110    254   84     103   [NAME]                james bond\n",
       "2       365    581   84     109    [ORG]           your city honda\n",
       "3        72    293  109     126    [DES]  sales leasing consultant\n",
       "4       413    540  264     279  [PHONE]                   818 547\n",
       "5       372    585  308     326  [EMAIL]  info@firstprintingca.com\n",
       "6       371    582  332     348    [WEB]   www.firstprintingca.com"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "img_tagging"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "cbbca991",
   "metadata": {},
   "outputs": [],
   "source": [
    "img_tagging[\"label\"] = img_tagging[\"label\"].apply(clean_text)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "f5e56107",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>left</th>\n",
       "      <th>right</th>\n",
       "      <th>top</th>\n",
       "      <th>bottom</th>\n",
       "      <th>label</th>\n",
       "      <th>token</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>group</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>110</td>\n",
       "      <td>254</td>\n",
       "      <td>84</td>\n",
       "      <td>103</td>\n",
       "      <td>name</td>\n",
       "      <td>james bond</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>365</td>\n",
       "      <td>581</td>\n",
       "      <td>84</td>\n",
       "      <td>109</td>\n",
       "      <td>org</td>\n",
       "      <td>your city honda</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>72</td>\n",
       "      <td>293</td>\n",
       "      <td>109</td>\n",
       "      <td>126</td>\n",
       "      <td>des</td>\n",
       "      <td>sales leasing consultant</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>413</td>\n",
       "      <td>540</td>\n",
       "      <td>264</td>\n",
       "      <td>279</td>\n",
       "      <td>phone</td>\n",
       "      <td>818 547</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>372</td>\n",
       "      <td>585</td>\n",
       "      <td>308</td>\n",
       "      <td>326</td>\n",
       "      <td>email</td>\n",
       "      <td>info@firstprintingca.com</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>371</td>\n",
       "      <td>582</td>\n",
       "      <td>332</td>\n",
       "      <td>348</td>\n",
       "      <td>web</td>\n",
       "      <td>www.firstprintingca.com</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       left  right  top  bottom  label                     token\n",
       "group                                                           \n",
       "1       110    254   84     103   name                james bond\n",
       "2       365    581   84     109    org           your city honda\n",
       "3        72    293  109     126    des  sales leasing consultant\n",
       "4       413    540  264     279  phone                   818 547\n",
       "5       372    585  308     326  email  info@firstprintingca.com\n",
       "6       371    582  332     348    web   www.firstprintingca.com"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "img_tagging"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "856bd576",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x2c80a8b3400>"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "img_bb = image.copy()\n",
    "\n",
    "for l,r,t,b,label,token in img_tagging.values:\n",
    "    cv2.rectangle(img_bb, (l,t), (r,b), (0,255,0),2)\n",
    "    cv2.putText(img_bb, str(label), (l,t), cv2.FONT_HERSHEY_PLAIN, 1, (255,0,0), 2)\n",
    "    \n",
    "plt.imshow(img_bb)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b581247a",
   "metadata": {},
   "source": [
    "# Parser"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "87b9f327",
   "metadata": {},
   "outputs": [],
   "source": [
    "def parser(text,label):\n",
    "    if label == \"PHONE\":\n",
    "        text = text.lower()\n",
    "        text = re.sub(r\"\\D\",\"\",text)\n",
    "    \n",
    "    elif label == \"EMAIL\":\n",
    "        text = text.lower()\n",
    "        allow_special_char = \"@_.\\-\"\n",
    "        text = re.sub(r\"[^A-Za-z0-9{} ]\".format(allow_special_char),\"\",text)\n",
    "        \n",
    "    elif label == \"WEB\":\n",
    "        text = text.lower()\n",
    "        allow_special_char = \":/.%#\\-\"\n",
    "        text = re.sub(r\"[^A-Za-z0-9{} ]\".format(allow_special_char),\"\",text)\n",
    "        \n",
    "    elif label in (\"NAME\", \"DES\"):\n",
    "        text = text.lower()\n",
    "        allow_special_char = \":/.%#-\"\n",
    "        text = re.sub(r\"[^a-z ]\",\"\",text)\n",
    "        text = text.title()\n",
    "        \n",
    "    elif label == \"ORG\":\n",
    "        text = text.lower()\n",
    "        allow_special_char = \":/.%#-\"\n",
    "        text = re.sub(r\"[^a-z0-9 ]\",\"\",text)\n",
    "        text = text.title()\n",
    "        \n",
    "    return text"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "8b31744f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'Erol '"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "parser(\"Erol 123424\", \"NAME\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "04c2920d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'ierolsen@outlook.com'"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "parser(\"i(erols}en)@outlook.com\", \"EMAIL\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b5a1ed0f",
   "metadata": {},
   "source": [
    "# Entities"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "b06df88f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>level</th>\n",
       "      <th>page_num</th>\n",
       "      <th>block_num</th>\n",
       "      <th>par_num</th>\n",
       "      <th>line_num</th>\n",
       "      <th>word_num</th>\n",
       "      <th>left</th>\n",
       "      <th>top</th>\n",
       "      <th>width</th>\n",
       "      <th>height</th>\n",
       "      <th>conf</th>\n",
       "      <th>text</th>\n",
       "      <th>end</th>\n",
       "      <th>start</th>\n",
       "      <th>token</th>\n",
       "      <th>label</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>110</td>\n",
       "      <td>84</td>\n",
       "      <td>74</td>\n",
       "      <td>19</td>\n",
       "      <td>96</td>\n",
       "      <td>james</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>james</td>\n",
       "      <td>B-NAME</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>193</td>\n",
       "      <td>84</td>\n",
       "      <td>61</td>\n",
       "      <td>18</td>\n",
       "      <td>96</td>\n",
       "      <td>bond</td>\n",
       "      <td>10</td>\n",
       "      <td>6</td>\n",
       "      <td>bond</td>\n",
       "      <td>I-NAME</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>365</td>\n",
       "      <td>84</td>\n",
       "      <td>60</td>\n",
       "      <td>19</td>\n",
       "      <td>96</td>\n",
       "      <td>your</td>\n",
       "      <td>15</td>\n",
       "      <td>11</td>\n",
       "      <td>your</td>\n",
       "      <td>B-ORG</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>434</td>\n",
       "      <td>84</td>\n",
       "      <td>53</td>\n",
       "      <td>25</td>\n",
       "      <td>96</td>\n",
       "      <td>city</td>\n",
       "      <td>20</td>\n",
       "      <td>16</td>\n",
       "      <td>city</td>\n",
       "      <td>I-ORG</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>496</td>\n",
       "      <td>84</td>\n",
       "      <td>85</td>\n",
       "      <td>19</td>\n",
       "      <td>96</td>\n",
       "      <td>honda</td>\n",
       "      <td>26</td>\n",
       "      <td>21</td>\n",
       "      <td>honda</td>\n",
       "      <td>I-ORG</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  level page_num block_num par_num line_num word_num left top width height  \\\n",
       "0     5        1         1       1        1        1  110  84    74     19   \n",
       "1     5        1         1       1        1        2  193  84    61     18   \n",
       "2     5        1         1       1        1        3  365  84    60     19   \n",
       "3     5        1         1       1        1        4  434  84    53     25   \n",
       "4     5        1         1       1        1        5  496  84    85     19   \n",
       "\n",
       "  conf   text  end  start  token   label  \n",
       "0   96  james    5      0  james  B-NAME  \n",
       "1   96   bond   10      6   bond  I-NAME  \n",
       "2   96   your   15     11   your   B-ORG  \n",
       "3   96   city   20     16   city   I-ORG  \n",
       "4   96  honda   26     21  honda   I-ORG  "
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dataframe_info.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "56b00b9b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>token</th>\n",
       "      <th>label</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>james</td>\n",
       "      <td>B-NAME</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>bond</td>\n",
       "      <td>I-NAME</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>your</td>\n",
       "      <td>B-ORG</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>city</td>\n",
       "      <td>I-ORG</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>honda</td>\n",
       "      <td>I-ORG</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>sales</td>\n",
       "      <td>B-DES</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>leasing</td>\n",
       "      <td>I-DES</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>consultant</td>\n",
       "      <td>I-DES</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>4718</td>\n",
       "      <td>O</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>san</td>\n",
       "      <td>O</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>fernando</td>\n",
       "      <td>O</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>rd</td>\n",
       "      <td>O</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>glendale</td>\n",
       "      <td>O</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>ca</td>\n",
       "      <td>O</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>91204</td>\n",
       "      <td>O</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>bus</td>\n",
       "      <td>O</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>818</td>\n",
       "      <td>B-PHONE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>547</td>\n",
       "      <td>I-PHONE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>fax</td>\n",
       "      <td>O</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>818</td>\n",
       "      <td>O</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>547</td>\n",
       "      <td>O</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>info@firstprintingca.com</td>\n",
       "      <td>B-EMAIL</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>www.firstprintingca.com</td>\n",
       "      <td>B-WEB</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                       token    label\n",
       "0                      james   B-NAME\n",
       "1                       bond   I-NAME\n",
       "2                       your    B-ORG\n",
       "3                       city    I-ORG\n",
       "4                      honda    I-ORG\n",
       "5                      sales    B-DES\n",
       "6                    leasing    I-DES\n",
       "7                 consultant    I-DES\n",
       "8                       4718        O\n",
       "9                        san        O\n",
       "10                  fernando        O\n",
       "11                        rd        O\n",
       "12                  glendale        O\n",
       "13                        ca        O\n",
       "14                     91204        O\n",
       "15                       bus        O\n",
       "16                       818  B-PHONE\n",
       "17                       547  I-PHONE\n",
       "18                       fax        O\n",
       "19                       818        O\n",
       "20                       547        O\n",
       "21  info@firstprintingca.com  B-EMAIL\n",
       "22   www.firstprintingca.com    B-WEB"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dataframe_info[[\"token\", \"label\"]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "e79cf846",
   "metadata": {},
   "outputs": [],
   "source": [
    "info_array = dataframe_info[[\"token\", \"label\"]].values\n",
    "entities = dict(NAME=[], ORG=[], DES=[], PHONE=[], EMAIL=[], WEB=[])\n",
    "\n",
    "previous = \"O\"\n",
    "for token, label in info_array:\n",
    "    #print(token, label)\n",
    "    bio_tag = label[0]\n",
    "    label_tag = label[2:]\n",
    "    #print(bio_tag, label_tag)\n",
    "    \n",
    "    # parse the token\n",
    "    text = parser(token, label_tag)\n",
    "    \n",
    "    if bio_tag in (\"B\", \"I\"):\n",
    "        \n",
    "        if previous != label_tag:\n",
    "            entities[label_tag].append(text)\n",
    "            \n",
    "        else:\n",
    "            if bio_tag == \"B\":\n",
    "                entities[label_tag].append(text)\n",
    "            else:\n",
    "                if label_tag in (\"NAME\", \"ORG\", \"DES\"):\n",
    "                    entities[label_tag][-1] = entities[label_tag][-1] + \" \" + text\n",
    "                else:\n",
    "                    entities[label_tag][-1] = entities[label_tag][-1] + text\n",
    "                \n",
    "    previous = label_tag"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "1b582f6a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'NAME': ['James Bond'],\n",
       " 'ORG': ['Your City Honda'],\n",
       " 'DES': ['Sales Leasing Consultant'],\n",
       " 'PHONE': ['818547'],\n",
       " 'EMAIL': ['info@firstprintingca.com'],\n",
       " 'WEB': ['www.firstprintingca.com']}"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "entities"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a7ac6f3e",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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