Abstract
The work described in this paper is about the automatic detection and extraction of causal relations that are explicitly expressed in Modern Standard Arabic (MSA) texts. In this initial study, a set of linguistic patterns was derived to indicate the presence of cause-effect information in sentences from open domain texts. The patterns were constructed based on a set of syntactic features which was acquired by analyzing a large untagged Arabic corpus so that parts of the sentence representing the cause and those representing the effect can be distinguished. To the best of researchers knowledge, no previous studies have dealt this type of relation for the Arabic language.
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Sadek, J. (2013). Automatic Detection of Arabic Causal Relations. In: Métais, E., Meziane, F., Saraee, M., Sugumaran, V., Vadera, S. (eds) Natural Language Processing and Information Systems. NLDB 2013. Lecture Notes in Computer Science, vol 7934. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38824-8_48
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DOI: https://doi.org/10.1007/978-3-642-38824-8_48
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