An improved extraction pattern representation model for automatic IE pattern acquisition

Authors:
Kiyoshi Sudo;Satoshi Sekine;Ralph Grishman
Affiliations:
New York University, New York, NY;New York University, New York, NY;New York University, New York, NY
Venue:
ACL '03 Proceedings of the 41st Annual Meeting on Association for Computational Linguistics - Volume 1
Year:
2003

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Abstract

Several approaches have been described for the automatic unsupervised acquisition 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 dependency chain. The effect of these alternative 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 subtrees of dependency trees. We describe a discovery procedure for this model and demonstrate experimentally an improvement in recall using Subtree patterns.