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LREC
2008

Exploiting the Role of Position Feature in Chinese Relation Extraction

9 years 3 months ago
Exploiting the Role of Position Feature in Chinese Relation Extraction
Relation extraction is the task of finding pre-defined semantic relations between two entities or entity mentions from text. Many methods, such as feature-based and kernel-based methods, have been proposed in the literature. Among them, feature-based methods draw much attention from researchers. However, to the best of our knowledge, existing feature-based methods did not explicitly incorporate the position feature and no in-depth analysis was conducted in this regard. In this paper, we define and exploit nine types of position information between two named entity mentions and then use it along with other features in a multi-class classification framework for Chinese relation extraction. Experiments on the ACE 2005 data set show that the position feature is more effective than the other recognized features like entity type/subtype and character-based N-gram context. Most important, it can be easily captured and does not require as much effort as applying deep natural language processi...
Peng Zhang, Wenjie Li, Furu Wei, Qin Lu, Yuexian H
Added 29 Oct 2010
Updated 29 Oct 2010
Type Conference
Year 2008
Where LREC
Authors Peng Zhang, Wenjie Li, Furu Wei, Qin Lu, Yuexian Hou
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