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.
The output is then discriminatively reranked REF to select the best analysis.
Coarse-To-Fine N-Best Parsing And MaxEnt Discriminative Reranking
Annual Meeting Of The Association For Computational Linguistics
Computer Science