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released
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Linux
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NameTag 2

1. Introduction

NameTag is an open-source tool for named entity recognition (NER). NameTag identifies proper names in text and classifies them into predefined categories, such as names of persons, locations, organizations, etc.

NameTag 2 also recognizes nested named entities (nested NER) and as of 2019, it achieves state of the art in Czech, English, Dutch and Spanish and nearly state of the art in German (Straková et al. 2019).

NameTag is available as an online demo NameTag Online Demo and web service NameTag Web Service hosted by LINDAT/CLARIN.

The linguistic models are free for non-commercial use and distributed under CC BY-NC-SA license, although for some models the original data used to create the model may impose additional licensing conditions.

NameTag is versioned using Semantic Versioning.

Copyright 2020 by Institute of Formal and Applied Linguistics, Faculty of Mathematics and Physics, Charles University in Prague, Czech Republic.

2. Release

NameTag 2 is currently available from the LINDAT NameTag Web Service:

3. Models

The individual models are described on a NameTag Models page.

4. License

The associated models and data are licensed under CC BY-NC-SA, although for some models the original data used to create the model may impose additional licensing conditions.

If you use this tool for scientific work, please give us credit by referencing NameTag website and Straková et al. 2019 (see BibTeX for referencing).

5. Acknowledgements

Acknowledgements for the individual language models are listed in NameTag Models page.

The work described herein has been supported by OP VVV VI LINDAT/CLARIN project of the Ministry of Education, Youth and Sports of the Czech Republic (project CZ.02.1.01/0.0/0.0/16 013/0001781) and it has been supported and has been using language resources developed by the LINDAT/CLARIN project of the Ministry of Education, Youth and Sports of the Czech Republic (project LM2015071). It has further been supported by PROGRES Q18 of the Charles University and by PROGRES Q48 of the Charles University.

5.1. Publications

Straková Jana, Straka Milan, Hajič Jan: Neural Architectures for Nested NER through Linearization. In: Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics, Copyright © Association for Computational Linguistics, Stroudsburg, PA, USA, ISBN 978-1-950737-48-2, pp. 5326-5331, 2019.

@inproceedings{StrakovaStrakaHajicACL2019,
  author    = {Jana Straková and Milan Straka and Jan Hajič},
  year      = 2019,
  title     = {Neural Architectures for Nested NER through Linearization},
  booktitle = {Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics},
  pages     = {5326--5331},
  publisher = {Association for Computational Linguistics},
  address   = {Stroudsburg, PA, USA},
  isbn      = {978-1-950737-48-2},
}

6. Contact

Authors:

NameTag website.

NameTag LINDAT/CLARIN entry.

7. Persistent Identifier

If you prefer to reference NameTag by a persistent identifier (PID), you can use http://hdl.handle.net/11858/00-097C-0000-0023-43CE-E.

Screenshot: