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  • 标题:Coordination Analysis Using Global Structural Constraints and Alignment-based Local Features
  • 本地全文:下载
  • 作者:Kazuo Hara ; Masashi Shimbo ; Yuji Matsumoto
  • 期刊名称:人工知能学会論文誌
  • 印刷版ISSN:1346-0714
  • 电子版ISSN:1346-8030
  • 出版年度:2010
  • 卷号:25
  • 期号:5
  • 页码:560-569
  • DOI:10.1527/tjsai.25.560
  • 出版社:The Japanese Society for Artificial Intelligence
  • 摘要:We propose a hybrid approach to coordinate structure analysis that combines a simple grammar to ensure consistent global structure of coordinations in a sentence, and features based on sequence alignment to capture local symmetry of conjuncts. The weight of the alignment-based features, which in turn determines the score of coordinate structures, is optimized by perceptron training on a given corpus. A bottom-up chart parsing algorithm efficiently finds the best scoring structure, taking both nested or non-overlapping flat coordinations into account. We demonstrate that our approach outperforms existing parsers in coordination scope detection on the Genia corpus.
  • 关键词:natural language processing ; coordination ; sequence alignment
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