articleJun 21, 2014Closed access

Learning Character-level Representations for Part-of-Speech Tagging

IBM Research - Brazil

Abstract

Distributed word representations have recently been proven to be an invaluable resource for NLP. These representations are normally learned using neural networks and capture syntactic and semantic information about words. Informa-tion about word morphology and shape is nor-mally ignored when learning word representa-tions. However, for tasks like part-of-speech tag-ging, intra-word information is extremely use-ful, specially when dealing with morphologically rich languages. In this paper, we propose a deep neural network that learns character-level repre-sentation of words and associate them with usual word representations to perform POS tagging. Using the proposed approach, while avoiding the use of any…

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Authors

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Topics & keywords

Keywords
  • Treebank
  • Computer science
  • Natural language processing
  • Artificial intelligence
  • Word (group theory)
  • Character (mathematics)
  • Feature (linguistics)
  • Part-of-speech tagging
UN Sustainable Development Goals
  • Quality Education
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