Semantic passage segmentation based on sentence topics for question answering

  • Authors:
  • Hyo-Jung Oh;Sung Hyon Myaeng;Myung-Gil Jang

  • Affiliations:
  • Electronics and Telecommunications Research Institute (ETRI), 161 Gajeong-dong, Yuseong-gu, Daejeon 305-700, Republic of Korea and School of Engineering, Information and Communications University, ...;School of Engineering, Information and Communications University, 119 Munjiro, Yuseong-gu, Daejeon 305-732, Republic of Korea;Electronics and Telecommunications Research Institute (ETRI), 161 Gajeong-dong, Yuseong-gu, Daejeon 305-700, Republic of Korea

  • Venue:
  • Information Sciences: an International Journal
  • Year:
  • 2007

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Abstract

We propose a semantic passage segmentation method for a Question Answering (QA) system. We define a semantic passage as sentences grouped by semantic coherence, determined by the topic assigned to individual sentences. Topic assignments are done by a sentence classifier based on a statistical classification technique, Maximum Entropy (ME), combined with multiple linguistic features. We ran experiments to evaluate the proposed method and its impact on application tasks, passage retrieval and template-filling for question answering. The experimental result shows that our semantic passage retrieval method using topic matching is more useful than fixed length passage retrieval. With the template-filling task used for information extraction in the QA system, the value of the sentence topic assignment method was reinforced.