Advertisement

Causal Relation Extraction Using Cue Phrase and Lexical Pair Probabilities

  • Du-Seong Chang
  • Key-Sun Choi
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3248)

Abstract

This work aims to extract causal relations that exist between two events expressed by noun phrases or sentences. The previous works for the causality made use of causal patterns such as causal verbs. We concentrate on the information obtained from other causal event pairs. If two event pairs share some lexical pairs and one of them is revealed to be causally related, the causal probability of another event pair tends to increase. We introduce the lexical pair probability and the cue phrase probability. These probabilities are learned from raw corpus in unsupervised manner. With these probabilities and the Naive Bayes classifier, we try to resolve the causal relation extraction problem. Our inter-NP causal relation extraction shows the precision of 81.29%, that is 7.05% improvement over the baseline model. The proposed models are also applied to inter-sentence causal relation extraction.

Keywords

Causal Relation Noun Phrase Question Answering Event Pair Event Extraction 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. [2000]
    Chang, D.-S., Choi, K.-S.: Unsupervised learning of the dependency grammar using inside and outside probabilities, in Proceedings of the 12th Hangul and Korean Information Processing (2000) (in Korean)Google Scholar
  2. [2003]
    Girju, R.: Automatic Detection of Causal Relation for Question Answering. In: Proceeding of Workshop in the 41st Annual Meeting of the Association for Computational Linguistics Conference (2003)Google Scholar
  3. [2002]
    Girju, R., Moldovan, D.: Mining Answers for Causation Questions. In: Proceeding of AAAI Symposium on Mining Answers from Texts and Knowledge Bases (2002)Google Scholar
  4. [2003]
  5. [2003]
    Joins HealthCare Medical Encyclopedia, http://healthcare.joins.com/library
  6. [2000]
    Khoo, C.S.G., Chan, S., Niu, Y.: Extracting Causal Knowledge from a Medical Database Using Graphical Patterns. In: Proceedings of The 38th Annual Meeting of the Association for Computational Linguistics (2000)Google Scholar
  7. [1988]
    Khoo, C.S.G., Kornfit, J., Oddy, R.N., Myaeng, S.H.: Automatic Extraction of Cause-Effect Information from Newspaper Text without Knowledge-Based Inferencing. Literary and Linguistic Computing 13(4), 177–186 (1998)CrossRefGoogle Scholar
  8. [2002]
    Marcu, D., Echihabi, A.: An Unsupervised Approach to Recognizing Discourse Relations. In: Proceedings of the 40th Annual Meeting of the Association for Computational Linguistics Conference, Philadelphia, PA (2002)Google Scholar
  9. [2004]
    Medical Subject Heading (2004), http://www.nlm.nih.gov/mesh
  10. [1995]
    Miller, G.: WordNet: a Lexical Database. Communications of the ACM 38(11), 39–41 (1995)CrossRefGoogle Scholar
  11. [2003]
    Modovan, D.I., Pasca, M., Harabagiu, S.M., Surdeanu, M.: Performance Issues and Error Analysis in an Open-Domain Question Answering. ACM Transactions on Information Systems 21(2), 133–154 (2003)CrossRefGoogle Scholar
  12. [2002]
    Moldovan, D.I., Harabagiu, S.M., Girju, R., Morarescu, P., Lacatusu, F., Novischi, A., Badulescu, A., Bolohan, O.: LCC Tools for Question Answering. In: Proceedings of the 11th Text Retrieval Conference, NIST (2002)Google Scholar
  13. [2000]
    Nigram, K., McCallum, A.K., Thrun, S., Mitchell, T.: Text Classification from Labeled and Unlabeled Documents using EM. Machine Learning 39(2/3), 103–134 (2000)CrossRefGoogle Scholar
  14. [1997]
    Tapanainen, P., Jarvinen, T.: A non-projective dependency parser. In: Proceedings of the 5th Conference on Applied Natural Language Processing, Association for Computational Linguistics, pp. 64–71 (1997)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Du-Seong Chang
    • 1
  • Key-Sun Choi
    • 1
  1. 1.Department of Electrical Engineering & Computer ScienceKORTERM, BOLA, Korea Advanced Institute of Science and TechnologyDaejeonKorea

Personalised recommendations