An Improved Extraction Pattern Representation Model for Automatic IE Pattern Acquisition

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.

• Type: Conference
• Year: 2003
• Where: ACL
• Authors: Kiyoshi Sudo, Satoshi Sekine, Ralph Grishman
• Keywords: ACL 2003, ACL 2007, Automatic Unsupervised Acquisition, Particular Model, Several Approaches