Paper: A Simple Rule-Based Part Of Speech Tagger

ACL ID A92-1021
Title A Simple Rule-Based Part Of Speech Tagger
Venue Applied Natural Language Processing Conference
Session Main Conference
Year 1992
Authors
  • Eric Brill (University of Pennsylvania, Philadelphia PA)

Automatic part of speech tagging is an area of natural language processing where statistical techniques have been more successful than rule- based methods. In this paper, we present a sim- ple rule-based part of speech tagger which au- tomatically acquires its rules and tags with ac- curacy comparable to stochastic taggers. The rule-based tagger has many advantages over these taggers, including: a vast reduction in stored information required, the perspicuity of a small set of meaningful rules, ease of finding and implementing improvements to the tagger, and better portability from one tag set, cor- pus genre or language to another. Perhaps the biggest contribution of this work is in demon- strating that the stochastic method is not the only viable method for part of speech tagging. The fa...