articleJan 1, 2005GOLD OA
Coarse-to-fine n -best parsing and MaxEnt discriminative reranking
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Abstract
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.
Citation impact
887
total citations
- FWCI
- 81.37
- Percentile
- 100%
- References
- 21
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Authors
2Topics & keywords
Topics
Keywords
- Discriminative model
- Parsing
- Computer science
- Sentence
- Artificial intelligence
- Set (abstract data type)
- Natural language processing
- Generative grammar
UN Sustainable Development Goals
- Reduced inequalities
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