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      "execution_count": 2,
      "metadata": {
        "id": "agiIuXeasaS7"
      },
      "outputs": [],
      "source": [
        "import pandas as pd\n",
        "import numpy as np"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#mount drive\n",
        "from google.colab import drive\n",
        "drive.mount('/content/drive')\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "2hh9OId7vTsq",
        "outputId": "dc9de282-c6f1-41db-a2f0-a5d84be49948"
      },
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Drive already mounted at /content/drive; to attempt to forcibly remount, call drive.mount(\"/content/drive\", force_remount=True).\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Check folder files\n",
        "%cd \"/content/drive/Shareddrives/C23-PS139-ML/data\"\n",
        "%ls -al "
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "i-5haGFIzjrX",
        "outputId": "170a8e7c-a181-42e6-e662-c9d9bca7ff3c"
      },
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "/content/drive/Shareddrives/C23-PS139-ML/data\n",
            "total 77\n",
            "-rw------- 1 root root 77894 May 30 12:56 destination.csv\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# load dataset\n",
        "df = pd.read_csv('/content/drive/Shareddrives/C23-PS139-ML/data/destination.csv')\n",
        "df.head()"
      ],
      "metadata": {
        "colab": {
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      "execution_count": 5,
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              "                                             map_url  \\\n",
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              "4                                                NaN   \n",
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              "                                             img_url  rating  total_review  \\\n",
              "0  https://lh5.googleusercontent.com/p/AF1QipNwrj...     4.4          42.0   \n",
              "1  https://lh5.googleusercontent.com/p/AF1QipMrjA...     4.4         812.0   \n",
              "2  https://lh5.googleusercontent.com/p/AF1QipO9_3...     4.8          16.0   \n",
              "3  https://lh5.googleusercontent.com/p/AF1QipNXjx...     3.9        1127.0   \n",
              "4  https://lh5.googleusercontent.com/p/AF1QipMASi...     4.5        3561.0   \n",
              "\n",
              "  pricing                                            address  \\\n",
              "0     NaN  59V4+HH4, Kadipaten, Kraton, Yogyakarta City, ...   \n",
              "1     NaN  Teras, depan McD, Jl. Cipayung Raya No.69, Cip...   \n",
              "2     NaN  Gabugan No. 41A, RT.05/RW.15, Gabugan, Pandowo...   \n",
              "3     NaN  Jl. Jatinegara Timur II No.7, RT.12/RW.2, Rw. ...   \n",
              "4     NaN  Kediwung, Mangunan, Dlingo, Bantul Regency, Sp...   \n",
              "\n",
              "                 city                                           category  \\\n",
              "0     Kota Yogyakarta               {\"university\": \"4\", \"building\": \"4\"}   \n",
              "1  Kota Jakarta Timur  {\"price\": \"38\", \"area\": \"17\", \"mie_aceh\": \"14\"...   \n",
              "2    Kabupaten Sleman                                                 {}   \n",
              "3  Kota Jakarta Timur                                                 {}   \n",
              "4    Kabupaten Bantul  {\"sunrise\": \"482\", \"morning\": \"259\", \"fog\": \"2...   \n",
              "\n",
              "                                               about  \\\n",
              "0  {\"No accessibility\": \"wheelchair accessible pa...   \n",
              "1  {\"from_the_business\": \"identifies as women-own...   \n",
              "2                                                 {}   \n",
              "3                                                 {}   \n",
              "4                                                 {}   \n",
              "\n",
              "                                       opening_hours  keyword_category  \n",
              "0                                                 {}               NaN  \n",
              "1                                                 {}               NaN  \n",
              "2                                                 {}               NaN  \n",
              "3                                                 {}               NaN  \n",
              "4  {'Tuesday': 'Open 24 hours', 'Wednesday': 'Ope...               NaN  "
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              "      <th>0</th>\n",
              "      <td>8837ac4d-72cc-4b98-a9c4-3117e630642c</td>\n",
              "      <td>Tourism Village Duchy</td>\n",
              "      <td>https://www.google.com/maps/place/Tourism+Vill...</td>\n",
              "      <td>https://lh5.googleusercontent.com/p/AF1QipNwrj...</td>\n",
              "      <td>4.4</td>\n",
              "      <td>42.0</td>\n",
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              "      <td>59V4+HH4, Kadipaten, Kraton, Yogyakarta City, ...</td>\n",
              "      <td>Kota Yogyakarta</td>\n",
              "      <td>{\"university\": \"4\", \"building\": \"4\"}</td>\n",
              "      <td>{\"No accessibility\": \"wheelchair accessible pa...</td>\n",
              "      <td>{}</td>\n",
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              "      <td>aaf158b8-adb6-4e5d-92fe-c57038847404</td>\n",
              "      <td>Pondok Rasa Teras cipayung</td>\n",
              "      <td>https://www.google.com/maps/place/Pondok+Rasa+...</td>\n",
              "      <td>https://lh5.googleusercontent.com/p/AF1QipMrjA...</td>\n",
              "      <td>4.4</td>\n",
              "      <td>812.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>Teras, depan McD, Jl. Cipayung Raya No.69, Cip...</td>\n",
              "      <td>Kota Jakarta Timur</td>\n",
              "      <td>{\"price\": \"38\", \"area\": \"17\", \"mie_aceh\": \"14\"...</td>\n",
              "      <td>{\"from_the_business\": \"identifies as women-own...</td>\n",
              "      <td>{}</td>\n",
              "      <td>NaN</td>\n",
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              "      <th>2</th>\n",
              "      <td>b14ecb2f-cb9a-43d2-bce2-7389846d6955</td>\n",
              "      <td>Casa Familia</td>\n",
              "      <td>https://www.google.com/maps/place/Casa+Familia...</td>\n",
              "      <td>https://lh5.googleusercontent.com/p/AF1QipO9_3...</td>\n",
              "      <td>4.8</td>\n",
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              "      <td>Gabugan No. 41A, RT.05/RW.15, Gabugan, Pandowo...</td>\n",
              "      <td>Kabupaten Sleman</td>\n",
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              "      <th>3</th>\n",
              "      <td>accf30e5-1a24-470c-8c56-8c78ddf157ea</td>\n",
              "      <td>Penginapan Rio</td>\n",
              "      <td>https://www.google.com/maps/place/Penginapan+R...</td>\n",
              "      <td>https://lh5.googleusercontent.com/p/AF1QipNXjx...</td>\n",
              "      <td>3.9</td>\n",
              "      <td>1127.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>Jl. Jatinegara Timur II No.7, RT.12/RW.2, Rw. ...</td>\n",
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              "      <td>{}</td>\n",
              "      <td>{}</td>\n",
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              "      <td>NaN</td>\n",
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              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-0efe9c6e-af89-4bab-9b0b-b3ec546324d9')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
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              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
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              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
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              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
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              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-0efe9c6e-af89-4bab-9b0b-b3ec546324d9 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
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              "          const element = document.querySelector('#df-0efe9c6e-af89-4bab-9b0b-b3ec546324d9');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
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              "          dataTable['output_type'] = 'display_data';\n",
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              "  "
            ]
          },
          "metadata": {},
          "execution_count": 5
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "!pip install transformers"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "x8tMCivXzCP9",
        "outputId": "b201824f-0d2c-4d74-d501-e3558978a7aa"
      },
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n",
            "Collecting transformers\n",
            "  Downloading transformers-4.29.2-py3-none-any.whl (7.1 MB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m7.1/7.1 MB\u001b[0m \u001b[31m61.2 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hRequirement already satisfied: filelock in /usr/local/lib/python3.10/dist-packages (from transformers) (3.12.0)\n",
            "Collecting huggingface-hub<1.0,>=0.14.1 (from transformers)\n",
            "  Downloading huggingface_hub-0.14.1-py3-none-any.whl (224 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m224.5/224.5 kB\u001b[0m \u001b[31m21.1 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hRequirement already satisfied: numpy>=1.17 in /usr/local/lib/python3.10/dist-packages (from transformers) (1.22.4)\n",
            "Requirement already satisfied: packaging>=20.0 in /usr/local/lib/python3.10/dist-packages (from transformers) (23.1)\n",
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            "Collecting tokenizers!=0.11.3,<0.14,>=0.11.1 (from transformers)\n",
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            "Installing collected packages: tokenizers, huggingface-hub, transformers\n",
            "Successfully installed huggingface-hub-0.14.1 tokenizers-0.13.3 transformers-4.29.2\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from transformers import AutoTokenizer, AutoModelForTokenClassification\n",
        "from transformers import pipeline"
      ],
      "metadata": {
        "id": "7O5AXszNzASd"
      },
      "execution_count": 7,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "tokenizer1 = AutoTokenizer.from_pretrained(\"dslim/bert-base-NER\")\n",
        "model1 = AutoModelForTokenClassification.from_pretrained(\"dslim/bert-base-NER\")\n",
        "ner1 = pipeline(\"ner\", model=model1, tokenizer=tokenizer1)\n",
        "\n",
        "\n",
        "tokenizer = AutoTokenizer.from_pretrained(\"cahya/bert-base-indonesian-NER\")\n",
        "model = AutoModelForTokenClassification.from_pretrained(\"cahya/bert-base-indonesian-NER\")\n",
        "\n",
        "ner = pipeline(\"ner\", model=model, tokenizer=tokenizer)"
      ],
      "metadata": {
        "id": "yYGoBpOQzvux",
        "colab": {
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        "outputId": "2a2be534-dbb6-4009-b2c4-908947ab39a8"
      },
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Downloading (…)okenizer_config.json:   0%|          | 0.00/59.0 [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
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              "model_id": "ad038a1dbec445278cf80a0da15f1b03"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
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            ],
            "application/vnd.jupyter.widget-view+json": {
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            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
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            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
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            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
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            ],
            "application/vnd.jupyter.widget-view+json": {
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            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
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            ],
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              "version_major": 2,
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            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
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              "Downloading pytorch_model.bin:   0%|          | 0.00/433M [00:00<?, ?B/s]"
            ],
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            }
          },
          "metadata": {}
        },
        {
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            ],
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          },
          "metadata": {}
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            }
          },
          "metadata": {}
        },
        {
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          },
          "metadata": {}
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            ],
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              "model_id": "6dc0116824f64fe688384a51b0bbd5a4"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
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            ],
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              "version_major": 2,
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              "model_id": "ee94b50eb31744488b453bd328ca0b1a"
            }
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "example = \"Saya ingin liburan ke kulon progo selama tiga hari\"\n"
      ],
      "metadata": {
        "id": "cBP035yX6ZCA"
      },
      "execution_count": 10,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "ner_results = ner(example)\n",
        "# print(ner_results)\n",
        "ner_results"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "TYL_22ts5YDT",
        "outputId": "bc3a82d2-3bef-4c4a-ff7f-63b1fdd345ee"
      },
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "Asking to truncate to max_length but no maximum length is provided and the model has no predefined maximum length. Default to no truncation.\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[{'entity': 'B-LOC',\n",
              "  'score': 0.86469996,\n",
              "  'index': 5,\n",
              "  'word': 'kulon',\n",
              "  'start': 22,\n",
              "  'end': 27},\n",
              " {'entity': 'I-LOC',\n",
              "  'score': 0.90692097,\n",
              "  'index': 6,\n",
              "  'word': 'progo',\n",
              "  'start': 28,\n",
              "  'end': 33},\n",
              " {'entity': 'B-QTY',\n",
              "  'score': 0.9715217,\n",
              "  'index': 8,\n",
              "  'word': 'tiga',\n",
              "  'start': 41,\n",
              "  'end': 45},\n",
              " {'entity': 'I-QTY',\n",
              "  'score': 0.9737994,\n",
              "  'index': 9,\n",
              "  'word': 'hari',\n",
              "  'start': 46,\n",
              "  'end': 50}]"
            ]
          },
          "metadata": {},
          "execution_count": 11
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "ner_results[0]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "rkw_gqvEjG7h",
        "outputId": "3337b74f-2185-4ab0-fcab-5dfca3b2d2bb"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "{'entity': 'B-GPE',\n",
              " 'score': 0.98306733,\n",
              " 'index': 5,\n",
              " 'word': 'jakarta',\n",
              " 'start': 22,\n",
              " 'end': 29}"
            ]
          },
          "metadata": {},
          "execution_count": 38
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "ner_results = ner1(example1)\n",
        "print(ner_results)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "GMLU2XFz8SL2",
        "outputId": "c02653fd-aa39-45c1-907f-226fa5b374d6"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[{'entity': 'B-PER', 'score': 0.9990139, 'index': 4, 'word': 'Wolfgang', 'start': 11, 'end': 19}, {'entity': 'B-LOC', 'score': 0.999645, 'index': 9, 'word': 'Berlin', 'start': 34, 'end': 40}]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from transformers import pipeline\n",
        "\n",
        "pretrained_name = \"w11wo/indonesian-roberta-base-posp-tagger\"\n"
      ],
      "metadata": {
        "id": "lnQi9Dqf5Yey"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "nlp = pipeline(\n",
        "    \"token-classification\",\n",
        "    model=pretrained_name,\n",
        "    tokenizer=pretrained_name\n",
        ")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 241,
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            "1501ace5d3744d4babcdf19e89ba02f7",
            "c81d9e5c68fd470e97367a8c50af70fb",
            "d3324d2e74264d1fa726d56d0e0cc193"
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        },
        "id": "NWZhLk-O5YZR",
        "outputId": "ad242552-c8a4-437d-f718-1a09c4b04d65"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Downloading (…)lve/main/config.json:   0%|          | 0.00/1.67k [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
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              "model_id": "169870529d43420498dee165bce2dcc6"
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          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Downloading pytorch_model.bin:   0%|          | 0.00/496M [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "fffe0dc7eaeb407c9850a4e6390bb18b"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Downloading (…)okenizer_config.json:   0%|          | 0.00/327 [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "54edbbc1731c4731bc95a3d99fcafc7c"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Downloading (…)olve/main/vocab.json:   0%|          | 0.00/808k [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "d8e4a63a0bca49b39c1e525252c34934"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
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            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "9352a407164548a299d1aefef531955d"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Downloading (…)/main/tokenizer.json:   0%|          | 0.00/1.38M [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "bb837506aca6492baf75fe4dfae6d307"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
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            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
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              "model_id": "2cbad029e8d547feb13bc2c6bca14b46"
            }
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "kata =\"Aku lagi di Jogja. Aku ingin ke tempat yang ramai. Selain itu, aku ingin membeli barang-barang antik juga. Tolong tambahkan Parangtritis juga di jadwalnya ya\"\n",
        "nlp(kata)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "tG8nKPL05YWy",
        "outputId": "1ace8194-f219-4cb1-e9a6-c93fe6111cae"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[{'entity': 'B-PRN',\n",
              "  'score': 0.891672,\n",
              "  'index': 0,\n",
              "  'word': 'ĠAku',\n",
              "  'start': 0,\n",
              "  'end': 3},\n",
              " {'entity': 'B-ADV',\n",
              "  'score': 0.862793,\n",
              "  'index': 1,\n",
              "  'word': 'Ġlagi',\n",
              "  'start': 4,\n",
              "  'end': 8},\n",
              " {'entity': 'B-PPO',\n",
              "  'score': 0.9990965,\n",
              "  'index': 2,\n",
              "  'word': 'Ġdi',\n",
              "  'start': 9,\n",
              "  'end': 11},\n",
              " {'entity': 'B-NNP',\n",
              "  'score': 0.99689615,\n",
              "  'index': 3,\n",
              "  'word': 'ĠJogja',\n",
              "  'start': 12,\n",
              "  'end': 17},\n",
              " {'entity': 'B-NNP',\n",
              "  'score': 0.7313682,\n",
              "  'index': 4,\n",
              "  'word': '.',\n",
              "  'start': 17,\n",
              "  'end': 18},\n",
              " {'entity': 'B-PRN',\n",
              "  'score': 0.96657693,\n",
              "  'index': 5,\n",
              "  'word': 'ĠAku',\n",
              "  'start': 19,\n",
              "  'end': 22},\n",
              " {'entity': 'B-ADV',\n",
              "  'score': 0.9771648,\n",
              "  'index': 6,\n",
              "  'word': 'Ġingin',\n",
              "  'start': 23,\n",
              "  'end': 28},\n",
              " {'entity': 'B-PPO',\n",
              "  'score': 0.998552,\n",
              "  'index': 7,\n",
              "  'word': 'Ġke',\n",
              "  'start': 29,\n",
              "  'end': 31},\n",
              " {'entity': 'B-PRR',\n",
              "  'score': 0.89115834,\n",
              "  'index': 8,\n",
              "  'word': 'Ġtempat',\n",
              "  'start': 32,\n",
              "  'end': 38},\n",
              " {'entity': 'B-PRR',\n",
              "  'score': 0.99569905,\n",
              "  'index': 9,\n",
              "  'word': 'Ġyang',\n",
              "  'start': 39,\n",
              "  'end': 43},\n",
              " {'entity': 'B-ADJ',\n",
              "  'score': 0.9044545,\n",
              "  'index': 10,\n",
              "  'word': 'Ġramai',\n",
              "  'start': 44,\n",
              "  'end': 49},\n",
              " {'entity': 'B-NNP',\n",
              "  'score': 0.59824723,\n",
              "  'index': 11,\n",
              "  'word': '.',\n",
              "  'start': 49,\n",
              "  'end': 50},\n",
              " {'entity': 'B-CCN',\n",
              "  'score': 0.814967,\n",
              "  'index': 12,\n",
              "  'word': 'ĠSelain',\n",
              "  'start': 51,\n",
              "  'end': 57},\n",
              " {'entity': 'B-NNP',\n",
              "  'score': 0.69807816,\n",
              "  'index': 13,\n",
              "  'word': 'Ġitu',\n",
              "  'start': 58,\n",
              "  'end': 61},\n",
              " {'entity': 'B-NNP',\n",
              "  'score': 0.88813037,\n",
              "  'index': 14,\n",
              "  'word': ',',\n",
              "  'start': 61,\n",
              "  'end': 62},\n",
              " {'entity': 'B-PRN',\n",
              "  'score': 0.97935814,\n",
              "  'index': 15,\n",
              "  'word': 'Ġaku',\n",
              "  'start': 63,\n",
              "  'end': 66},\n",
              " {'entity': 'B-ADV',\n",
              "  'score': 0.982064,\n",
              "  'index': 16,\n",
              "  'word': 'Ġingin',\n",
              "  'start': 67,\n",
              "  'end': 72},\n",
              " {'entity': 'B-VBT',\n",
              "  'score': 0.98620087,\n",
              "  'index': 17,\n",
              "  'word': 'Ġmembeli',\n",
              "  'start': 73,\n",
              "  'end': 80},\n",
              " {'entity': 'B-NNO',\n",
              "  'score': 0.64908123,\n",
              "  'index': 18,\n",
              "  'word': 'Ġbarang',\n",
              "  'start': 81,\n",
              "  'end': 87},\n",
              " {'entity': 'B-NNO',\n",
              "  'score': 0.88329476,\n",
              "  'index': 19,\n",
              "  'word': '-',\n",
              "  'start': 87,\n",
              "  'end': 88},\n",
              " {'entity': 'B-NNO',\n",
              "  'score': 0.7287077,\n",
              "  'index': 20,\n",
              "  'word': 'barang',\n",
              "  'start': 88,\n",
              "  'end': 94},\n",
              " {'entity': 'B-NNO',\n",
              "  'score': 0.55157626,\n",
              "  'index': 21,\n",
              "  'word': 'Ġantik',\n",
              "  'start': 95,\n",
              "  'end': 100},\n",
              " {'entity': 'B-ADV',\n",
              "  'score': 0.41747996,\n",
              "  'index': 22,\n",
              "  'word': 'Ġjuga',\n",
              "  'start': 101,\n",
              "  'end': 105},\n",
              " {'entity': 'B-NNP',\n",
              "  'score': 0.9026728,\n",
              "  'index': 23,\n",
              "  'word': '.',\n",
              "  'start': 105,\n",
              "  'end': 106},\n",
              " {'entity': 'B-ADV',\n",
              "  'score': 0.23877065,\n",
              "  'index': 24,\n",
              "  'word': 'ĠTolong',\n",
              "  'start': 107,\n",
              "  'end': 113},\n",
              " {'entity': 'B-VBT',\n",
              "  'score': 0.55252516,\n",
              "  'index': 25,\n",
              "  'word': 'Ġtambahkan',\n",
              "  'start': 114,\n",
              "  'end': 123},\n",
              " {'entity': 'B-NNP',\n",
              "  'score': 0.98184884,\n",
              "  'index': 26,\n",
              "  'word': 'ĠParangtritis',\n",
              "  'start': 124,\n",
              "  'end': 136},\n",
              " {'entity': 'B-ADV',\n",
              "  'score': 0.99565697,\n",
              "  'index': 27,\n",
              "  'word': 'Ġjuga',\n",
              "  'start': 137,\n",
              "  'end': 141},\n",
              " {'entity': 'B-PPO',\n",
              "  'score': 0.9980392,\n",
              "  'index': 28,\n",
              "  'word': 'Ġdi',\n",
              "  'start': 142,\n",
              "  'end': 144},\n",
              " {'entity': 'B-NNO',\n",
              "  'score': 0.7808285,\n",
              "  'index': 29,\n",
              "  'word': 'Ġjadwalnya',\n",
              "  'start': 145,\n",
              "  'end': 154},\n",
              " {'entity': 'B-PAR',\n",
              "  'score': 0.8833419,\n",
              "  'index': 30,\n",
              "  'word': 'Ġya',\n",
              "  'start': 155,\n",
              "  'end': 157}]"
            ]
          },
          "metadata": {},
          "execution_count": 32
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "xO1Qu8rT5YUq"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# !pip install spacy"
      ],
      "metadata": {
        "id": "rmPjKcVi2OPX"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# !pip show spacy"
      ],
      "metadata": {
        "id": "Kb7j8jRN24uH"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# import spacy\n",
        "# from spacy import load, display\n",
        "# from spacy.util import minibatch, compounding\n",
        "# from pathlib import Path\n",
        "# import pickle\n",
        "# import random"
      ],
      "metadata": {
        "id": "3smiQewk2VHS"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "G_kCBuzP2pvu"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}