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kermitt2 committed Jan 5, 2020
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2 changes: 1 addition & 1 deletion LICENSE
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same "printed page" as the copyright notice for easier
identification within third-party archives.

Copyright 2008-2019 GROBID's contributors
Copyright 2008-2020 GROBID's contributors

Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
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4 changes: 2 additions & 2 deletions Readme.md
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Expand Up @@ -15,7 +15,7 @@ Visit the [GROBID documentation](http://grobid.readthedocs.org) for more detaile

GROBID (or Grobid, but not GroBid nor GroBiD) means GeneRation Of BIbliographic Data.

GROBID is a machine learning library for extracting, parsing and re-structuring raw documents such as PDF into structured XML/TEI encoded documents with a particular focus on technical and scientific publications. First developments started in 2008 as a hobby. In 2011 the tool has been made available in open source. Work on GROBID has been steady as a side project since the beginning and is expected to continue until at least 2020 :)
GROBID is a machine learning library for extracting, parsing and re-structuring raw documents such as PDF into structured XML/TEI encoded documents with a particular focus on technical and scientific publications. First developments started in 2008 as a hobby. In 2011 the tool has been made available in open source. Work on GROBID has been steady as a side project since the beginning and is expected to continue as such.

The following functionalities are available:

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title = {GROBID},
howpublished = {\url{https://github.com/kermitt2/grobid}},
publisher = {GitHub},
year = {2008 --- 2019},
year = {2008 --- 2020},
archivePrefix = {swh},
eprint = {1:dir:6a298c1b2008913d62e01e5bc967510500f80710}
}
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2 changes: 1 addition & 1 deletion doc/Introduction.md
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GROBID (or Grobid, but not GroBid nor GroBiD) means GeneRation Of BIbliographic Data.

GROBID is a machine learning library for extracting, parsing and re-structuring raw documents such as PDF into structured XML/TEI encoded documents with a particular focus on technical and scientific publications. First developments started in 2008 as a hobby. In 2011 the tool has been made available in open source. Work on GROBID has been steady as side project since the beginning and is expected to continue until at least 2020 :)
GROBID is a machine learning library for extracting, parsing and re-structuring raw documents such as PDF into structured XML/TEI encoded documents with a particular focus on technical and scientific publications. First developments started in 2008 as a hobby. In 2011 the tool has been made available in open source. Work on GROBID has been steady as side project since the beginning and is expected to continue as such.

The following functionalities are available:

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6 changes: 4 additions & 2 deletions doc/References.md
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To cite this work, you can simply refer to the github project:

```
GROBID (2008-2019) <https://github.com/kermitt2/grobid>
GROBID (2008-2020) <https://github.com/kermitt2/grobid>
```

(please do not include a particular person name to emphasize the project and tool!)
Expand All @@ -15,7 +15,7 @@ Here's a BibTeX entry:
title = {GROBID},
howpublished = {\url{https://github.com/kermitt2/grobid}},
publisher = {GitHub},
year = {2008 --- 2019},
year = {2008 --- 2020},
archivePrefix = {swh},
eprint = {1:dir:6a298c1b2008913d62e01e5bc967510500f80710}
}
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[GROBID in 20 slides](GROBID.pdf) (2012).

P. Lopez. Automatic Extraction and Resolution of Bibliographical References in Patent Documents. First Information Retrieval Facility Conference (IRFC), Vienna, May 2010. LNCS 6107, pp. 120-135. Springer, Heidelberg, 2010.

## Evaluation and usages

Joseph Boyd. [Automatic Metadata Extraction The High Energy Physics Use Case](https://preprints.cern.ch/record/2039361/files/CERN-THESIS-2015-105.pdf). Master Thesis, EPFL, Switzerland, 2015.
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2 changes: 1 addition & 1 deletion grobid-service/src/main/resources/web/index.html
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</div>

<footer>
<p><span style="color:#848484;">&copy; Grobid contributors - 2019 </span></p>
<p><span style="color:#848484;">&copy; Grobid contributors - 2020 </span></p>
</footer>
</div>

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