NDLI: Extracting Arabic Causal Relations Using Linguistic Patterns

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Extracting Arabic Causal Relations Using Linguistic Patterns

Content Provider	ACM Digital Library
Author	Meziane, Farid Sadek, Jawad
Copyright Year	2016
Abstract	Identifying semantic relations is a crucial step in discourse analysis and is useful for many applications in both language and speech technology. Automatic detection of $\textit{Causal}$ relations therefore has gained popularity in the literature within different frameworks. The aim of this article is the automatic detection and extraction of $\textit{Causal}$ relations that are explicitly expressed in Arabic texts. To fulfill this goal, a Pattern Recognizer model was developed to signal the presence of cause--effect information within sentences from nonspecific domain texts. This model incorporates approximately 700 linguistic patterns so that parts of the sentence representing the $\textit{cause}$ and those representing the $\textit{effect}$ can be distinguished. The patterns were constructed based on different sets of syntactic features by analyzing a large untagged Arabic corpus. In addition, the model was boosted with three independent algorithms to deal with certain types of grammatical particles that indicate causation. With this approach, the proposed model achieved an overall $\textit{recall}$ of 81% and a $\textit{precision}$ of 78%. Evaluation results revealed that the justification particles play a key role in detecting $\textit{Causal}$ relations. To the best of our knowledge, no previous studies have been dedicated to dealing with this type of relation in the Arabic language.
Starting Page	1
Ending Page	20
Page Count	20
File Format	PDF
ISSN	23754699
e-ISSN	23754702
DOI	10.1145/2800786
Volume Number	15
Issue Number	3
Journal	ACM Transactions on Asian and Low-Resource Language Information Processing (TALLIP)
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2016-03-08
Publisher Place	New York
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Arabic discourse relations Patterns matching Causal relations Information extraction
Content Type	Text
Resource Type	Article
Subject	Computer Science

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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