Paper: Counter-Training In Discovery Of Semantic Patterns

ACL ID P03-1044
Title Counter-Training In Discovery Of Semantic Patterns
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2003

This paper presents a method for unsu- pervised discovery of semantic patterns. Semantic patterns are useful for a vari- ety of text understanding tasks, in par- ticular for locating events in text for in- formation extraction. The method builds upon previously described approaches to iterative unsupervised pattern acquisition. One common characteristic of prior ap- proaches is that the output of the algorithm is a continuous stream of patterns, with gradually degrading precision. Our method differs from the previous pat- tern acquisition algorithms in that it intro- duces competition among several scenar- ios simultaneously. This provides natu- ral stopping criteria for the unsupervised learners, while maintaining good preci- sion levels at termination. We discuss the results of experimen...