Building and Evaluating Universal Named-Entity Recognition English corpus
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Abstract (arXiv)
This article presents the application of the Universal Named Entity framework to generate automatically annotated corpora. By using a workflow that extracts Wikipedia data and meta-data and DBpedia information, we generated an English dataset which is described and evaluated. Furthermore, we conducted a set of experiments to improve the annotations in terms of precision, recall, and F1-measure. The final dataset is available and the established workflow can be applied to any language with existing Wikipedia and DBpedia. As part of future research, we intend to continue improving the annotation process and extend it to other languages.
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References · 6
- 2018A Survey on Deep Learning for Named Entity Recognitioncited by 281
- 2019A Survey on Recent Advances in Named Entity Recognition from Deep Learning modelscited by 117
- 2017Weakly Supervised Cross-Lingual Named Entity Recognition via Effective Annotation and Representation Projectioncited by 36
- 2019Introducing RONEC -- the Romanian Named Entity Corpuscited by 12
- 2019Building a Massive Corpus for Named Entity Recognition using Free Open Data Sourcescited by 2
- 2020Evaluating Language Tools for Fifteen EU-official Under-resourced Languagescited by 1
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