2006 ACompositeKernelForRelExtr
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- (Zhang et al., 2006a) ⇒ Min Zhang, Jie Zhang, Jian Su, Guodong Zhou. (2006). “A Composite Kernel to Extract Relations between Entities with Both Flat and Structured Features.” In: Proceedings of COLING-ACL (ACL 2006). doi:10.3115/1220175.1220279
Subject Headings: Relation Recognition from Text Algorithm, ACE Benchmark Task
Notes
- It defines a Syntactic Path-Enclosed Subtree.
Cited By
2008
- (Sarawagi, 2008) ⇒ Sunita Sarawagi. (2008). “Information Extraction.” In: Foundations and Trends in Databases, 1(3). doi:10.1561/1900000003
Quotes
Abstract
This paper proposes a novel composite kernel for relation extraction. The composite kernel consists of two individual kernels: an entity kernel that allows for entity-related features and a convolution parse tree kernel that models syntactic information of relation examples. The motivation of our method is to fully utilize the nice properties of kernel methods to explore diverse knowledge for relation extraction. Our study illustrates that the composite kernel can effectively capture both flat and structured features without the need for extensive feature engineering, and can also easily scale to include more features. Evaluation on the ACE corpus shows that our method outperforms the previous best-reported methods and significantly outperforms previous two dependency tree kernels for relation extraction."
References
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| Author | volume | Date Value | title | type | journal | titleUrl | doi | note | year | |
|---|---|---|---|---|---|---|---|---|---|---|
| 2006 ACompositeKernelForRelExtr | Min Zhang Jian Su Jie Zhang GuoDong Zhou | A Composite Kernel to Extract Relations between Entities with Both Flat and Structured Features | Proceedings of COLING-ACL | http://acl.ldc.upenn.edu/P/P06/P06-1104.pdf | 10.3115/1220175.1220279 | 2006 |