Automatic Extraction of the Fine Category of Person Named Entities from Text Corpora
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概要
- 論文の詳細を見る
Named entities play an important role in many Natural Language Processing applications. Currently, most named entity recognition systems rely on a small set of general named entity (NE) types. Though some efforts have been proposed to expand the hierarchy of NE types, there are still a fixed number of NE types. In real applications, such as question answering or semantic search systems, users may be interested in more diverse specific NE types. This paper proposes a method to extract categories of person named entities from text documents. Based on Dual Iterative Pattern Relation Extraction method, we develop a more suitable model for solving our problem, and explore the generation of different pattern types. A method for validating whether a category is valid or not is proposed to improve the performance, and experiments on Wall Street Journal corpus give promising results.
- 社団法人電子情報通信学会の論文
- 2007-10-01
著者
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Nguyen Tri-thanh
School Of Information Science Japan Advanced Institute Of Science And Technology
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Shimazu Akira
School Of Information Science Japan Advanced Institute Of Science And Technology
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Shimazu Akira
Japan Advanced Inst. Sci. And Technol. Nomi‐shi Jpn
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