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Please use this identifier to cite or link to this item: http://hdl.handle.net/UCSP/15847
Title: Conditional Random Fields for Spanish Named Entity Recognition Using Unsupervised Features
Authors: Copara Zea, Jenny
Ochoa, Jose
Thorne, Camilo
Glavas, Goran
Keywords: Artificial intelligence;Image segmentation;Collocations;Conditional random field;Cross-lingual;Deep learning;Named entity recognition;NER for Spanish;Word collocations;Word representations;Random processes
Issue Date: 2016
Publisher: Springer Verlag
metadata.dc.relation.uri: https://www.scopus.com/inward/record.uri?eid=2-s2.0-84994131732&doi=10.1007%2f978-3-319-47955-2_15&partnerID=40&md5=f2f86b9030d7122aa4d20d5b3f39a658
Abstract: Unsupervised features based on word representations such as word embeddings and word collocations have shown to significantly improve supervised NER for English. In this work we investigate whether such unsupervised features can also boost supervised NER in Spanish. To do so, we use word representations and collocations as additional features in a linear chain Conditional Random Field (CRF) classifier. Experimental results (82.44% F-score on the CoNLL-2002 corpus) show that our approach is comparable to some state-of-art Deep Learning approaches for Spanish, in particular when using cross-lingual word representations. © Springer International Publishing AG 2016.
URI: http://repositorio.ucsp.edu.pe/handle/UCSP/15847
ISBN: urn:isbn:9783319479545
ISSN: 3029743
Appears in Collections:Artículos - Ciencia de la computación

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