@inproceedings{osenova-simov-2024-bulgarian,
    title = "{B}ulgarian {P}arla{M}int 4.0 corpus as a testset for Part-of-speech tagging and Named Entity Recognition",
    author = "Osenova, Petya  and
      Simov, Kiril",
    editor = "Fiser, Darja  and
      Eskevich, Maria  and
      Bordon, David",
    booktitle = "Proceedings of the IV Workshop on Creating, Analysing, and Increasing Accessibility of Parliamentary Corpora (ParlaCLARIN) @ LREC-COLING 2024",
    month = may,
    year = "2024",
    address = "Torino, Italia",
    publisher = "ELRA and ICCL",
    url = "https://aclanthology.org/2024.parlaclarin-1.4",
    pages = "30--35",
    abstract = "The paper discusses some fine-tuned models for the tasks of part-of-speech tagging and named entity recognition. The fine-tuning was performed on the basis of an existing BERT pre-trained model and two newly pre-trained BERT models for Bulgarian that are cross-tested on the domain of the Bulgarian part of the ParlaMint corpora as a new domain. In addition, a comparison has been made between the performance of the new fine-tuned BERT models and the available results from the Stanza-based model which the Bulgarian part of the ParlaMint corpora has been annotated with. The observations show the weaknesses in each model as well as the common challenges.",
}

The paper discusses some fine-tuned models for the tasks of part-of-speech tagging and named entity recognition. The fine-tuning was performed on the basis of an existing BERT pre-trained model and two newly pre-trained BERT models for Bulgarian that are cross-tested on the domain of the Bulgarian part of the ParlaMint corpora as a new domain. In addition, a comparison has been made between the performance of the new fine-tuned BERT models and the available results from the Stanza-based model which the Bulgarian part of the ParlaMint corpora has been annotated with. The observations show the weaknesses in each model as well as the common challenges.
Osenova, Petya Simov, Kiril
Bulgarian ParlaMint 4.0 corpus as a testset for Part-of-speech tagging and Named Entity Recognition