Embeddings for Named Entity Recognition in Geoscience Portuguese Literature

Bernardo Consoli, Joaquim Santos, Diogo Gomes, Fabio Cordeiro, Renata Vieira, Viviane Moreira

Abstract
This work focuses on Portuguese Named Entity Recognition (NER) in the Geology domain. The only domain-specific dataset in the Portuguese language annotated for NER is the GeoCorpus. Our approach relies on BiLSTM-CRF neural networks (a widely used type of network for this area of research) that use vector and tensor embedding representations. Three types of embedding models were used (Word Embeddings, Flair Embeddings, and Stacked Embeddings) under two versions (domain-specific and generalized). The domain specific Flair Embeddings model was originally trained with a generalized context in mind, but was then fine-tuned with domain-specific Oil and Gas corpora, as there simply was not enough domain corpora to properly train such a model. Each of these embeddings was evaluated separately, as well as stacked with another embedding. Finally, we achieved state-of-the-art results for this domain with one of our embeddings, and we performed an error analysis on the language model that achieved the best results. Furthermore, we investigated the effects of domain-specific versus generalized embeddings.
Anthology ID:
2020.lrec-1.568
Volume:
Proceedings of the Twelfth Language Resources and Evaluation Conference
Month:
May
Year:
2020
Address:
Marseille, France
Editors:
Nicoletta Calzolari, Frédéric Béchet, Philippe Blache, Khalid Choukri, Christopher Cieri, Thierry Declerck, Sara Goggi, Hitoshi Isahara, Bente Maegaard, Joseph Mariani, Hélène Mazo, Asuncion Moreno, Jan Odijk, Stelios Piperidis
Venue:
LREC
SIG:
Publisher:
European Language Resources Association
Note:
Pages:
4625–4630
Language:
English
URL:
https://aclanthology.org/2020.lrec-1.568
DOI:
Bibkey:
Cite (ACL):
Bernardo Consoli, Joaquim Santos, Diogo Gomes, Fabio Cordeiro, Renata Vieira, and Viviane Moreira. 2020. Embeddings for Named Entity Recognition in Geoscience Portuguese Literature. In Proceedings of the Twelfth Language Resources and Evaluation Conference, pages 4625–4630, Marseille, France. European Language Resources Association.
Cite (Informal):
Embeddings for Named Entity Recognition in Geoscience Portuguese Literature (Consoli et al., LREC 2020)
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PDF:
https://preview.aclanthology.org/naacl24-info/2020.lrec-1.568.pdf
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