Extracting Arabic causal relations using linguistic patterns
Journal article
Authors | Sadek, J and Meziane, F. |
---|---|
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 Causal relations therefore has gained popularity in the literature within different frameworks. The aim of this paper is the automatic detection and extraction of 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 non-specific domain texts. This model incorporates approximately 700 linguistic patterns so that parts of the sentence representing the cause and those representing the 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 recall of 81% and a precision of 78%. Evaluation results revealed that the justification particles play a key role in detecting Causal relations. |
Keywords | And Phrases; Patterns matching; Arabic discourse relations; Causal relations; Information extraction |
Year | 2016 |
Journal | ACM Transactions on Asian and Low-Resource Language Information Processing |
Journal citation | Vol 15 (Issue 3, Article: 14), p. 1–20 |
Publisher | Association for Computing Machinery |
ISSN | 2375-4699 |
2375-4702 | |
Digital Object Identifier (DOI) | https://doi.org/10.1145/2800786 |
Web address (URL) | http://dx.doi.org/10.1145/2800786 |
Output status | Published |
Publication dates | |
Online | 08 Mar 2016 |
Publication process dates | |
Accepted | 01 Jan 2015 |
Deposited | 05 Jun 2023 |
https://repository.derby.ac.uk/item/9z142/extracting-arabic-causal-relations-using-linguistic-patterns
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