2005 ExtractingRelsIntegInforUsingKernelMethods
- (Zhao & Grishman, 2005) ⇒ Shubin Zhao, and Ralph Grishman. (2005). “Extracting Relations with Integrated Information Using Kernel Methods.” In: Proceedings of ACL Conference (ACL 2005).
Subject Headings: Relation Detection from Text Algorithm, ACE Benchmark Task
Notes
Cited By
2006
- (Zhang et al., 2006b) ⇒ Min Zhang, Jie Zhang, and Jian Su. (2006). “Exploring Syntactic Features for Relation Extraction using a Convolution Tree Kernel.” In: Proceedings of HLT Conference (HLT 2006).
- QUOTE: Zhao and Grishman (2005) define a feature based composite kernel to integrate diverse features. Their kernel displays very good performance on the 2004 version of ACE corpus. Since this is a feature-based kernel, all the features used in the kernel have to be explicitly enumerated. Similar with the feature-based method, they also represent the tree feature as a link path between two entities. Therefore, we wonder whether their performance improvement is mainly due to the explicitly incorporation of diverse linguistic features instead of the kernel method itself.
Quotes
Abstract
Entity relation detection is a form of information extraction that finds predefined relations between pairs of entities in text. This paper describes a relation detection approach that combines clues from different levels of syntactic processing using kernel methods. Information from three different levels of processing is considered: tokenization, sentence parsing and deep dependency analysis. Each source of information is represented by kernel functions. Then composite kernels are developed to integrate and extend individual kernels so that processing errors occurring at one level can be overcome by information from other levels. We present an evaluation of these methods on the 2004 ACE relation detection task, using Support Vector Machines, and show that each level of syntactic processing contributes useful information for this task. When evaluated on the official test data, our approach produced very competitive ACE value scores. We also compare the SVM with KNN on different kernels.
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| Author | volume | Date Value | title | type | journal | titleUrl | doi | note | year | |
|---|---|---|---|---|---|---|---|---|---|---|
| 2005 ExtractingRelsIntegInforUsingKernelMethods | Ralph Grishman Shubin Zhao | Extracting Relations with Integrated Information Using Kernel Methods | Proceedings of ACL Conference | http://acl.ldc.upenn.edu/P/P05/P05-1052.pdf | 2005 |