usmiva/bg_ner_bsnlp

Tasks

• token-classification

Citation text from the card

@inproceedings{piskorski-etal-2019-second,
   title = "The Second Cross-Lingual Challenge on Recognition, Normalization, Classification, and Linking of Named Entities across {S}lavic Languages",
   author = "Piskorski, Jakub  and Laskova, Laska  and Marci{\'n}czuk, Micha{\l}  and Pivovarova, Lidia  and P{\v{r}}ib{\'a}{\v{n}}, Pavel  
   and Steinberger, Josef  and Yangarber, Roman",
   booktitle = "Proceedings of the 7th Workshop on Balto-Slavic Natural Language Processing",
   month = aug,
   year = "2019",
   address = "Florence, Italy",
   publisher = "Association for Computational Linguistics",
   url = "https://www.aclweb.org/anthology/W19-3709",
   pages = "63--74"
   }

   @inproceedings{marinova-etal-2020-reconstructing,
    title = "Reconstructing {NER} Corpora: a Case Study on {B}ulgarian",
    author = "Marinova, Iva  and
      Laskova, Laska  and
      Osenova, Petya  and
      Simov, Kiril  and
      Popov, Alexander",
    booktitle = "Proceedings of the Twelfth Language Resources and Evaluation Conference",
    month = may,
    year = "2020",
    address = "Marseille, France",
    publisher = "European Language Resources Association",
    url = "https://aclanthology.org/2020.lrec-1.571",
    pages = "4647--4652",
    abstract = "The paper reports on the usage of deep learning methods for improving a Named Entity Recognition (NER) training corpus and for predicting and annotating new types in a test corpus. We show how the annotations in a type-based corpus of na

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