Spanish NER with Word Representations and Conditional Random Fields

NEWS@ACM Pub Date : 2016-08-01 DOI:10.18653/v1/W16-2705
J. Copara, J. Ochoa, Camilo Thorne, Goran Glavas
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引用次数: 18

Abstract

Word Representations such as word embeddings have been shown to significantly improve (semi-)supervised NER for the English language. In this work we investigate whether word representations can also boost (semi-)supervised NER in Spanish. To do so, we use word representations as additional features in a linear chain Conditional Random Field (CRF) classifier. Experimental results (82.44 Fscore on the CoNLL-2002 corpus) show that our approach is comparable to some state-of-the-art Deep Learning approaches for Spanish, in particular when using
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具有词表示和条件随机场的西班牙语NER
单词表示(如单词嵌入)已被证明可以显著改善英语语言的(半)监督NER。在这项工作中,我们研究了单词表征是否也可以提高西班牙语的(半)监督NER。为此,我们在线性链条件随机场(CRF)分类器中使用单词表示作为附加特征。实验结果(CoNLL-2002语料库上的82.44分)表明,我们的方法可以与一些最先进的西班牙语深度学习方法相媲美,特别是在使用
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