Please use this identifier to cite or link to this item:
|Title:||Conditional Random Fields for Spanish Named Entity Recognition Using Unsupervised Features|
|Authors:||Copara Zea, Jenny|
|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|
|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.|
|Appears in Collections:||Artículos de investigación|
Files in This Item:
There are no files associated with this item.
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.