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Causal Relation Extraction Using Cue Phrase and Lexical Pair Probabilities

TitleCausal Relation Extraction Using Cue Phrase and Lexical Pair Probabilities
Publication TypeBook Chapter
Year of Publication2005
AuthorsChang, D-S, Choi, K-S
EditorSu, K-Y, Tsujii, J’ichi, Lee, J-H, Kwong, O
Book TitleNatural Language Processing – IJCNLP 2004
Series TitleLecture Notes in Computer Science
Volume3248
Pagination61-70
PublisherSpringer
CityBerlin / Heidelberg
ISBN Number978-3-540-24475-2
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.

URLhttp://blog.swrc.kaist.ac.kr/paper/395.pdf
DOI10.1007/978-3-540-30211-7_7