Named Entity Recognition involves automatically identifying and classifying entities such as persons, places, and organizations, and it is a very important task in Information Extraction. Conditional Random Fields is a probabilistic method for structured prediction, which can be used in this task. This paper presents the use of Conditional Random Fields for Named Entity Recognition in Portuguese texts considering the term classification obtained by a Local Grammar as an additional informed feature. Local grammars are handmade rules to identify named entities within the text. The Golden Collection of the First and Second HAREM considered as a reference for Named Entity Recognition systems in Portuguese were used as training and test sets respectively. The results obtained outperform the results competitive systems reported in the literature.
@InProceedings{PIROVANI18.309, author = {Juliana Pirovani and Elias Oliveira}, title = "{Portuguese Named Entity Recognition using Conditional Random Fields and Local Grammars}", booktitle = {Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018)}, year = {2018}, month = {May 7-12, 2018}, address = {Miyazaki, Japan}, editor = {Nicoletta Calzolari (Conference chair) and Khalid Choukri and Christopher Cieri and Thierry Declerck and Sara Goggi and Koiti Hasida and Hitoshi Isahara and Bente Maegaard and Joseph Mariani and Hélène Mazo and Asuncion Moreno and Jan Odijk and Stelios Piperidis and Takenobu Tokunaga}, publisher = {European Language Resources Association (ELRA)}, isbn = {979-10-95546-00-9}, language = {english} }
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