PetroGold – Corpus padrão ouro para o domínio do petróleo
Resumo
Este trabalho descreve a criação do PetroGold, um treebank padrão ouro para o domínio do óleo & gás. O material é composto por teses, dissertações e monografias, contém 9.127 frases (253.640 tokens) e conta com anotação morfossintática de dependências segundo a abordagem Universal Dependencies. Detalhamos alguns dos desafios linguísticos do domínio para a anotação sintática e verificamos a qualidade do material produzido por meio de uma avaliação intrínseca: utilizando um modelo criado pela ferramenta UDPipe, o corpus leva a 90,65%, 88,53% e 82,88% de acertos conforme as medidas UAS, LAS e CLAS, respectivamente.
Referências
Antonitsch, A., Figueira, A., Amaral, D., Fonseca, E., Vieira, R., and Collovini, S. (2016). Summ-it++: an enriched version of the summ-it corpus. In Calzolari, N., Choukri, K., Declerck, T., Goggi, S., Grobelnik, M., Maegaard, B., Mariani, J., Mazo, H., Moreno, A., Odijk, J., and Piperidis, S., editors, Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC 2016), pages 2047–2051, Paris, France. European Language Resources Association (ELRA).
Cohen, K. B., Verspoor, K., Fort, K., Funk, C., Bada, M., Palmer, M., and Hunter, L. E. (2017). The colorado richly annotated full text (craft) corpus: Multi-model annotation in the biomedical domain. In Handbook of Linguistic Annotation, pages 1379–1394. Springer.
de Souza, E. and Freitas, C. (2021). Et: A workstation for querying, editing and evaluating annotated corpora. In Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing: System Demonstrations, Online. Association for Computational Linguistics.
Duran, M. S. and Aluísio, S. (2011). Propbank-br: a brazilian portuguese corpus annotated with semantic role labels. In Proceedings of the 8th Brazilian Symposium in Information and Human Language Technology.
Evelyn, W. F. D. (2021). Dos termos às entidades no domínio de petróleo. Master’s thesis, PPGEL/PUC-Rio.
Freitas, C., Carvalho, P., Oliveira, H. G., Mota, C., and Santos, D. (2010). Second HAREM: advancing the state of the art of named entity recognition in Portuguese. In Calzolari, N., Choukri, K., Maegaard, B., Mariani, J., Odijk, J., Piperidis, S., Rosner, M., and Tapias, D., editors, Proceedings of the International Conference on Language Resources and Evaluation (LREC 2010), pages 3630–3637. European Language Resources Association.
Freitas, C., Rocha, P., and Bick, E. (2008). Um mundo novo na oresta sintá (c) tica–o treebank do português. Calidoscópio, 6(3):142–148.
Gamallo, P., Garcia, M., and Fernández-Lanza, S. (2012). Dependency-based open information extraction. In Proceedings of the joint workshop on unsupervised and semisupervised learning in NLP, pages 10–18.
Gomes, D., Cordeiro, F., and Evsukoff, A. (2018). Word embeddings em português para o domínio específico de óleo e gás. In Proceedings of the 19th Rio oil & gas expo and conference, page 10.
Nivre, J., De Marneffe, M.-C., Ginter, F., Goldberg, Y., Hajic, J., Manning, C. D., McDonald, R., Petrov, S., Pyysalo, S., Silveira, N., et al. (2016). Universal dependencies v1: A multilingual treebank collection. In Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC’16), pages 1659–1666.
Qi, P., Zhang, Y., Zhang, Y., Bolton, J., and Manning, C. D. (2020). Stanza: A Python In Proceedings of natural language processing toolkit for many human languages. the 58th Annual Meeting of the Association for Computational Linguistics: System Demonstrations.
Rademaker, A., Chalub, F., Real, L., Freitas, C., Bick, E., and de Paiva, V. (2017). Universal dependencies for portuguese. In Proceedings of the Fourth International Conference on Dependency Linguistics (Depling 2017), pages 197–206.
Silveira, A., de Souza, E., Cavalcanti, T., and Freitas, C. (2019). Do pdf ao txt: Desafios na extração de informação em textos técnico-científicos. In VI Workshop de Iniciação Científica em Tecnologia da Informação e da Linguagem Humana (TILic 2019).
Straka, M., Hajic, J., and Straková, J. (2016). Udpipe: trainable pipeline for processing conll-u files performing tokenization, morphological analysis, pos tagging and parsing. In Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC’16), pages 4290–4297.
Thompson, P., Ananiadou, S., and Tsujii, J. (2017). The genia corpus: Annotation levels and applications. In Handbook of Linguistic Annotation, pages 1395–1432. Springer.
Zeman, D., Hajic, J., Popel, M., Potthast, M., Straka, M., Ginter, F., Nivre, J., and Petrov, S. (2018). Conll 2018 shared task: Multilingual parsing from raw text to universal dependencies. In Proceedings of the CoNLL 2018 Shared Task: Multilingual parsing from raw text to universal dependencies, pages 1–21.
Cohen, K. B., Verspoor, K., Fort, K., Funk, C., Bada, M., Palmer, M., and Hunter, L. E. (2017). The colorado richly annotated full text (craft) corpus: Multi-model annotation in the biomedical domain. In Handbook of Linguistic Annotation, pages 1379–1394. Springer.
de Souza, E. and Freitas, C. (2021). Et: A workstation for querying, editing and evaluating annotated corpora. In Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing: System Demonstrations, Online. Association for Computational Linguistics.
Duran, M. S. and Aluísio, S. (2011). Propbank-br: a brazilian portuguese corpus annotated with semantic role labels. In Proceedings of the 8th Brazilian Symposium in Information and Human Language Technology.
Evelyn, W. F. D. (2021). Dos termos às entidades no domínio de petróleo. Master’s thesis, PPGEL/PUC-Rio.
Freitas, C., Carvalho, P., Oliveira, H. G., Mota, C., and Santos, D. (2010). Second HAREM: advancing the state of the art of named entity recognition in Portuguese. In Calzolari, N., Choukri, K., Maegaard, B., Mariani, J., Odijk, J., Piperidis, S., Rosner, M., and Tapias, D., editors, Proceedings of the International Conference on Language Resources and Evaluation (LREC 2010), pages 3630–3637. European Language Resources Association.
Freitas, C., Rocha, P., and Bick, E. (2008). Um mundo novo na oresta sintá (c) tica–o treebank do português. Calidoscópio, 6(3):142–148.
Gamallo, P., Garcia, M., and Fernández-Lanza, S. (2012). Dependency-based open information extraction. In Proceedings of the joint workshop on unsupervised and semisupervised learning in NLP, pages 10–18.
Gomes, D., Cordeiro, F., and Evsukoff, A. (2018). Word embeddings em português para o domínio específico de óleo e gás. In Proceedings of the 19th Rio oil & gas expo and conference, page 10.
Nivre, J., De Marneffe, M.-C., Ginter, F., Goldberg, Y., Hajic, J., Manning, C. D., McDonald, R., Petrov, S., Pyysalo, S., Silveira, N., et al. (2016). Universal dependencies v1: A multilingual treebank collection. In Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC’16), pages 1659–1666.
Qi, P., Zhang, Y., Zhang, Y., Bolton, J., and Manning, C. D. (2020). Stanza: A Python In Proceedings of natural language processing toolkit for many human languages. the 58th Annual Meeting of the Association for Computational Linguistics: System Demonstrations.
Rademaker, A., Chalub, F., Real, L., Freitas, C., Bick, E., and de Paiva, V. (2017). Universal dependencies for portuguese. In Proceedings of the Fourth International Conference on Dependency Linguistics (Depling 2017), pages 197–206.
Silveira, A., de Souza, E., Cavalcanti, T., and Freitas, C. (2019). Do pdf ao txt: Desafios na extração de informação em textos técnico-científicos. In VI Workshop de Iniciação Científica em Tecnologia da Informação e da Linguagem Humana (TILic 2019).
Straka, M., Hajic, J., and Straková, J. (2016). Udpipe: trainable pipeline for processing conll-u files performing tokenization, morphological analysis, pos tagging and parsing. In Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC’16), pages 4290–4297.
Thompson, P., Ananiadou, S., and Tsujii, J. (2017). The genia corpus: Annotation levels and applications. In Handbook of Linguistic Annotation, pages 1395–1432. Springer.
Zeman, D., Hajic, J., Popel, M., Potthast, M., Straka, M., Ginter, F., Nivre, J., and Petrov, S. (2018). Conll 2018 shared task: Multilingual parsing from raw text to universal dependencies. In Proceedings of the CoNLL 2018 Shared Task: Multilingual parsing from raw text to universal dependencies, pages 1–21.
Publicado
29/11/2021
Como Citar
SOUZA, Elvis de; SILVEIRA, Aline; CAVALCANTI, Tatiana; CASTRO, Maria Clara; FREITAS, Cláudia.
PetroGold – Corpus padrão ouro para o domínio do petróleo. In: SIMPÓSIO BRASILEIRO DE TECNOLOGIA DA INFORMAÇÃO E DA LINGUAGEM HUMANA (STIL), 13. , 2021, Evento Online.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2021
.
p. 29-38.
DOI: https://doi.org/10.5753/stil.2021.17781.
