Parsing natural language queries for life science knowledge

  • Authors:
  • Tadayoshi Hara;Yuka Tateisi;Jin-Dong Kim;Yusuke Miyao

  • Affiliations:
  • National Institute of Informatics, Hitotsubashi, Chiyoda-ku, Tokyo, Japan;Kogakuin University, Nishi-shinjuku, Shinjuku-ku, Tokyo, Japan;Database Center for Life Science, Yayoi, Bunkyo-ku, Tokyo, Japan;National Institute of Informatics, Hitotsubashi, Chiyoda-ku, Tokyo, Japan

  • Venue:
  • BioNLP '11 Proceedings of BioNLP 2011 Workshop
  • Year:
  • 2011

Quantified Score

Hi-index 0.00

Visualization

Abstract

This paper presents our preliminary work on adaptation of parsing technology toward natural language query processing for biomedical domain. We built a small treebank of natural language queries, and tested a state-of-the-art parser, the results of which revealed that a parser trained on Wall-Street-Journal articles and Medline abstracts did not work well on query sentences. We then experimented an adaptive learning technique, to seek the chance to improve the parsing performance on query sentences. Despite the small scale of the experiments, the results are encouraging, enlightening the direction for effective improvement.