Paper: An Improved Parser For Data-Oriented Lexical-Functional Analysis

ACL ID P00-1009
Title An Improved Parser For Data-Oriented Lexical-Functional Analysis
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2000
Authors
  • Rens Bod (University of Leeds, Leeds UK; University of Amsterdam, Amsterdam The Netherlands)

We present an LFG-DOP parser which uses fragments from LFG-annotated sentences to parse new sentences. Experiments with the Verbmobil and Homecentre corpora show that (1) Viterbi n best search performs about 100 times faster than Monte Carlo search while both achieve the same accuracy; (2) the DOP hypothesis which states that parse accuracy increases with increasing frag- ment size is confirmed for LFG-DOP; (3) LFG- DOP's relative frequency estimator performs worse than a discounted frequency estimator; and (4) LFG-DOP significantly outperforms Tree- DOP if evaluated on tree structures only.