Paper: Inferring Parts Of Speech For Lexical Mappings Via The Cyc KB

ACL ID C04-1191
Title Inferring Parts Of Speech For Lexical Mappings Via The Cyc KB
Venue International Conference on Computational Linguistics
Session Main Conference
Year 2004
Authors

We present an automatic approach to learn- ing criteria for classifying the parts-of-speech used in lexical mappings. This will fur- ther automate our knowledge acquisition sys- tem for non-technical users. The criteria for the speech parts are based on the types of the denoted terms along with morphological and corpus-based clues. Associations among these and the parts-of-speech are learned us- ing the lexical mappings contained in the Cyc knowledge base as training data. With over 30 speech parts to choose from, the classifier achieves good results (77.8% correct). Ac- curate results (93.0%) are achieved in the special case of the mass-count distinction for nouns. Comparable results are also obtained using OpenCyc (73.1% general and 88.4% mass-count).