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README.md Update README.md Jan 21, 2019

README.md

finer-data

Introduction

The directory data contains a corpus of Finnish technology related news articles with a manually prepared named entity annotation (digitoday.2014.csv). The text material was extracted from the archives of Digitoday, a Finnish online technology news source (www.digitoday.fi). The corpus consists of 953 articles (193,742 word tokens) with six named entity classes (organization, location, person, product, event, and date). The corpus is available for research purposes and can be readily used for development of NER systems for Finnish. The corpus is described in the article

"A Finnish News Corpus for Named Entity Recognition" (in review)

Experiments

The repository also contains the Digitoday (digitoday.2015.test.csv) and Wikipedia (wikipedia.test.csv) evaluation sets employed in the experiments of the article

"A Finnish News Corpus for Named Entity Recognition"

The training and development sets formed of digitoday.2014.csv employed in the experiments can be found from files digitoday.2014.train.csv and digitoday.2014.dev.csv, respectively.

Finally, the directory experiments contains the predictions of systems FiNER, Gungor-NN, and Sohrab-NN in the paper "A Finnish News Corpus for Named Entity Recognition" on the Digitoday and Wikipedia evaluation sets.

FiNER:

urn.fi/urn:nbn:fi:lb-2018091301

Gungor-NN:

@InProceedings{C18-1177,
  author = 	"G{\"{u}}ng{\"{o}}r, Onur
		and {\"{U}}sk{\"{u}}darli, Suzan
		and G{\"{u}}ng{\"{o}}r, Tunga",
  title = 	"Improving Named Entity Recognition by Jointly Learning to Disambiguate Morphological Tags",
  booktitle = 	"Proceedings of the 27th International Conference on Computational Linguistics",
  year = 	"2018",
  publisher = 	"Association for Computational Linguistics",
  pages = 	"2082--2092",
  location = 	"Santa Fe, New Mexico, USA",
  url = 	"http://aclweb.org/anthology/C18-1177"
}

Sohrab-NN:

@InProceedings{D18-1309,
  author = 	"Sohrab, Mohammad Golam
		and Miwa, Makoto",
  title = 	"Deep Exhaustive Model for Nested Named Entity Recognition",
  booktitle = 	"Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing",
  year = 	"2018",
  publisher = 	"Association for Computational Linguistics",
  pages = 	"2843--2849",
  location = 	"Brussels, Belgium",
  url = 	"http://aclweb.org/anthology/D18-1309"
}

License

The Digitoday material is licensed under CC BY-ND-NC 1.0 and the Wikipedia material is licensed under CC BY-SA 3.0

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