Skip to main content

Classification of Multiple-Sentence Questions

  • Conference paper
Natural Language Processing – IJCNLP 2005 (IJCNLP 2005)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3651))

Included in the following conference series:

Abstract

Conventional QA systems cannot answer to the questions composed of two or more sentences. Therefore, we aim to construct a QA system that can answer such multiple-sentence questions. As the first stage, we propose a method for classifying multiple-sentence questions into question types. Specifically, we first extract the core sentence from a given question text. We use the core sentence and its question focus in question classification. The result of experiments shows that the proposed method improves F-measure by 8.8% and accuracy by 4.4%.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Sasaki, Y., Isozaki, H., Hirao, T., Kokuryou, K., Maeda, E.: NTT’s QA Systems for NTCIR QAC-1. Working Notes, NTCIR Workshop 3, Tokyo, pp. 63–70 (2002)

    Google Scholar 

  2. Xu, J., Licuanan, A., Weischedel, R.M.: TREC 2003 QA at BBN: Answering Definitional Questions. In: TREC 2003, pp. 98–106 (2003)

    Google Scholar 

  3. Li, X., Roth, D.: Learning Question Classifiers. In: COLING 2002, Taipei, Taiwan, pp. 556–562 (2002)

    Google Scholar 

  4. Zukerman, I., Horvitz, E.: Using Machine Learning Techniques to Interpret WH-questions. In: ACL 2001, Toulouse, France, pp. 547–554 (2001)

    Google Scholar 

  5. Ittycheriah, A., Franz, M., Zhu, W.-J., Ratnaparkhi, A.: Question Answering Using Maximum Entropy Components. In: NAACL 2001, pp. 33–39 (2001)

    Google Scholar 

  6. Suzuki, J.: Kernels for Structured Data in Natural Language Processing, Doctor Thesis, Nara Institute of Science and Technology (2005)

    Google Scholar 

  7. Zhang, D., Lee, W.S.: Question Classification using Support Vector Machines. In: SIGIR, Toronto, Canada, pp. 26–32 (2003)

    Google Scholar 

  8. Moldovan, D., Harabagiu, S., Pasca, M., Mihalcea, R., Goodrum, R., Girju, R., Rus, V.: Lasso: A Tool for Surfing the Answer Net. In: TREC-8, pp. 175–184 (1999)

    Google Scholar 

  9. Ikehara, S., Miyazaki, M., Shirai, S., Yokoo, A., Nakaiwa, H., Ogura, K., Oyama, Y., Hayashi, Y.(eds.): The Semantic System, vol. 1, Goi-Taikei – A Japanese Lexicon, Iwanami Shoten (1997) (in Japanese)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2005 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Tamura, A., Takamura, H., Okumura, M. (2005). Classification of Multiple-Sentence Questions. In: Dale, R., Wong, KF., Su, J., Kwong, O.Y. (eds) Natural Language Processing – IJCNLP 2005. IJCNLP 2005. Lecture Notes in Computer Science(), vol 3651. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11562214_38

Download citation

  • DOI: https://doi.org/10.1007/11562214_38

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-29172-5

  • Online ISBN: 978-3-540-31724-1

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics