Coarse-to-Fine n-Best Parsing and MaxEnt Discriminative Reranking

Discriminative reranking is one method for constructing high-performance statistical parsers (Collins, 2000). A discriminative reranker requires a source of candidate parses for each sentence. This paper describes a simple yet novel method for constructing sets of 50-best parses based on a coarse-to-fine generative parser (Charniak, 2000). This method generates 50-best lists that are of substantially higher quality than previously obtainable. We used these parses as the input to a MaxEnt reranker (Johnson et al., 1999; Riezler et al., 2002) that selects the best parse from the set of parses for each sentence, obtaining an f-score of 91.0% on sentences of length 100 or less.

• Publication year

  2005

• Venue

  Annual Meeting of the Association for Computational Linguistics

• Publication date

  2005-06-25

• Fields of study

  Computer Science

• Identifiers
  DOI 10.3115/1219840.1219862
• 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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