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Question Answering: CNLP at the TREC-9 Question Answering Track
School of Information Studies: Faculty Scholarship
  • Anne R. Diekema, Utah State University
  • Xiaoyong Liu, Syracuse University
  • Jiangping Chen, Syracuse University
  • Hudong Wang, Syracuse University
  • Nancy McCracken, Syracuse University
Document Type
  • CNLP,
  • TREC-9,
  • question answering track
This paper describes a question answering system that automatically finds answers to questions in a large collection of documents. The prototype CNLP question answering system was developed for participation in the TREC-9 question answering track. The system uses a two-stage retrieval approach to answer finding based on keyword and named entity matching. Results indicate that the system ranks correct answers high (mostly rank 1), provided that an answer to the question was found. Performance figures and further analyses are included.
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Citation Information
Anne R. Diekema, Xiaoyong Liu, Jiangping Chen, Hudong Wang, et al.. "Question Answering: CNLP at the TREC-9 Question Answering Track" (2000)
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Creative Commons Attribution 3.0