TAILIEUCHUNG - Báo cáo khoa học: "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. . | An Improved Extraction Pattern Representation Model for Automatic IE Pattern Acquisition Kiyoshi Sudo Satoshi Sekine and Ralph Grishman Department of Computer Science New York University 715 Broadway 7th Floor New York nY 10003 USA sudo sekine grishman @ 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. 1 Introduction Information Extraction IE is the process of identifying events or actions of interest and their participating entities from a text. As the field of IE has developed the focus of study has moved towards automatic knowledge acquisition for information extraction including domain-specific lexicons Riloff 1993 Riloff and Jones 1999 and extraction patterns Riloff 1996 Yangarber et al. 2000 Sudo et al. 2001 . In particular methods have recently emerged for the acquisition of event extraction patterns without corpus annotation in view of the cost of manual labor for annotation. However there has been little study of alternative representation models of extraction patterns for unsupervised acquisition. In the prior work on extraction pattern acquisition the representation model of the patterns was based on a fixed set of pattern templates Riloff 1996 or predicate-argument relations such as subject-verb and object-verb Yangarber et al. 2000 . The model of our previous work Sudo et al. 2001 was based on the paths from predicate nodes in dependency trees. In this paper we discuss the limitations of prior .

• Báo cáo khoa học
• An Improved Extraction
• Pattern Representation Model
• Automatic IE Pattern Acquisition
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• xử lý ngôn ngữ tự nhiên
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