Syntactic Processing Using Global Discriminative Learning and Beam-Search Decoding

This tutorial discusses a framework for incremental left-to-right structured predication, which makes use of global discriminative learning and beam-search decoding. The method has been applied to a wide range of NLP tasks in recent years, and achieved competitive accuracies and efficiencies. We give an introduction to the algorithms and efficient implementations, and discuss their applications to a range of NLP tasks.

• Publication year

  2014

• Venue

  Annual Meeting of the Association for Computational Linguistics

• Publication date

  2014-06-01

• Fields of study

  Linguistics, Computer Science

• Identifiers
  DOI 10.3115/v1/P14-6008
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

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