Paper: An Improved Extraction Pattern Representation Model For Automatic IE Pattern Acquisition

ACL ID P03-1029
Title An Improved Extraction Pattern Representation Model For Automatic IE Pattern Acquisition
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2003
Authors

Several approaches have been described for the automatic unsupervised acquisi- tion of patterns for information extraction. Each approach is based on a particular model for the patterns to be acquired, such as a predicate-argument structure or a de- pendency chain. The effect of these al- ternative models has not been previously studied. In this paper, we compare the prior models and introduce a new model, the Subtree model, based on arbitrary sub- trees of dependency trees. We describe a discovery procedure for this model and demonstrate experimentally an improve- ment in recall using Subtree patterns.