Paper: Extending A Broad-Coverage Parser For A General NLP Toolkit

ACL ID C02-1159
Title Extending A Broad-Coverage Parser For A General NLP Toolkit
Venue International Conference on Computational Linguistics
Session Main Conference
Year 2002
Authors

With the rapid growth of real world applications for NLP systems, there is a genuine demand for a general toolkit from which programmers with no linguistic knowledge can build specific NLP systems. Such a toolkit should have a parser that is general enough to be used across domains, and yet accurate enough for each specific application. In this paper, we describe a parser that extends a broad-coverage parser, Minipar (Lin, 2001), with an adaptable shallow parser so as to achieve both generality and accuracy in handling domain specific NL problems. We test this parser on our corpus and the results show that the accuracy is significantly higher than a system that uses Minipar alone.