Paper: Unsupervised Discovery of Generic Relationships Using Pattern Clusters and its Evaluation by Automatically Generated SAT Analogy Questions

ACL ID P08-1079
Title Unsupervised Discovery of Generic Relationships Using Pattern Clusters and its Evaluation by Automatically Generated SAT Analogy Questions
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2008
Authors

We present a novel framework for the dis- covery and representation of general semantic relationships that hold between lexical items. We propose that each such relationship can be identified with a cluster of patterns that cap- tures this relationship. We give a fully unsu- pervised algorithm for pattern cluster discov- ery, which searches, clusters and merges high- frequency words-based patterns around ran- domly selected hook words. Pattern clusters can be used to extract instances of the corre- sponding relationships. To assess the quality of discovered relationships, we use the pattern clusters to automatically generate SAT anal- ogy questions. We also compare to a set of known relationships, achieving very good re- sults in both methods. The evaluation (done in both English and Russi...