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)


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.


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.


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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

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