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2018 | OriginalPaper | Buchkapitel

Portuguese Named Entity Recognition Using LSTM-CRF

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Autoren: Pedro Vitor Quinta de Castro, Nádia Félix Felipe da Silva, Anderson da Silva Soares

Verlag: Springer International Publishing

Erschienen in: Computational Processing of the Portuguese Language

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Abstract

Named Entity Recognition is a challenging Natural Language Processing task for a language as rich as Portuguese. For this task, a Deep Learning architecture based on bidirectional Long Short-Term Memory with Conditional Random Fields has shown state-of-the-art performance for English, Spanish, Dutch and German languages. In this work, we evaluate this architecture and perform the tuning of hyperparameters for Portuguese corpora. The results achieve state-of-the-art performance using the optimal values for them, improving the results obtained for Portuguese language to up to 5 points in the F1 score.

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https://www.wikipedia.org/.

This is because I indicates an internal token in the named entity, and O indicates a non-entity token, which means that anything after it would be the starting token of an entity or another non-entity token. Since the first token of a named entity starts with B, according to the IOB scheme, it is not possible that an internal entity token follows a non-entity token.

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Titel

Portuguese Named Entity Recognition Using LSTM-CRF

Buch

Computational Processing of the Portuguese Language

Print ISBN: 978-3-319-99721-6

Electronic ISBN: 978-3-319-99722-3

https://doi.org/10.1007/978-3-319-99722-3

DOI

https://doi.org/10.1007/978-3-319-99722-3_9

Autoren:

Pedro Vitor Quinta de Castro
Nádia Félix Felipe da Silva
Anderson da Silva Soares

Verlag

Springer International Publishing

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