Matches in ScholarlyData for { <https://w3id.org/scholarlydata/inproceedings/lrec2008/papers/540> ?p ?o. }
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- 540 creator furu-wei.
- 540 creator peng-zhang.
- 540 creator qin-lu.
- 540 creator wenjie-li.
- 540 creator yuexian-hou.
- 540 type InProceedings.
- 540 label "Exploiting the Role of Position Feature in Chinese Relation Extraction".
- 540 sameAs 540.
- 540 abstract "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 processing.".
- 540 hasAuthorList authorList.
- 540 hasTopic Linguistics.
- 540 isPartOf proceedings.
- 540 keyword "Information Extraction, Information Retrieval".
- 540 keyword "Knowledge representation".
- 540 keyword "Text mining".
- 540 title "Exploiting the Role of Position Feature in Chinese Relation Extraction".