Extracting Knowledge from an Arabic-English Machine-Readable Dictionary Using Information Extraction
This paper presents a method for automatically extracting lexical information from a machine-readable version of the Arabic-English Al-Mawrid dictionary. Using n-gram and keyword-in-context (KWIC) analysis to discover lexical patterns, and hand-crafted rule-based information extraction, the study achieved high precision across all information types, high recall for synonyms, but low recall for other types. The Al-Mawrid dictionary was found to contain substantial derivations, synonyms, domain labels, and hyponym/hypernym relations.
[2606.28457] Extracting Knowledge from an Arabic-English Machine-Readable Dictionary Using Information Extraction
[Submitted on 26 Jun 2026]
Title:Extracting Knowledge from an Arabic-English Machine-Readable Dictionary Using Information Extraction
View a PDF of the paper titled Extracting Knowledge from an Arabic-English Machine-Readable Dictionary Using Information Extraction, by Diaa M. Fayed and 3 other authors
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Abstract:Natural language processing (NLP) applications need large and rich amount of linguistic knowledge. Furthermore, electronic language sources such as dictionaries, encyclopedia, and corpora became available. So, automatic methods are emerged to extract lexical information from those sources to overcome the knowledge acquisition bottleneck. We presented a method to automatically extract lexical information from a machine-readable version of the Arabic-English Al-Mawrid dictionary. We used n-gram analysis and key-word-in-context (KWIC) analysis to discover lexical patterns that manifest morphologic, syntactic, or semantic information. Then, we used hand-crafted rule-based information extraction to extract that information. Furthermore, we used punctuation marks and some heuristics to extract a set of synonyms in a subentry. This study registered high precision for all types of information, high recall for synonyms, and low recall for the other information. The study also showed that the Al-Mawrid has significant amount of derivations (morphologic information) and synonyms, domain labels, and hyponym/hypernym relations (semantic information).
Comments: 9 pages, 7 figures, 4 tables, Conference version,CITALA 2014: 5th International Conference on Arabic Language Processing,Oujda, Morocco, 26-27 November 2014. Paper listed in archived accepted papers: this https URL Original conference site defunct: this http URL No proceedings PDF is publicly available
Subjects:
Computation and Language (cs.CL)
Cite as: arXiv:2606.28457 [cs.CL]
(or arXiv:2606.28457v1 [cs.CL] for this version)
https://doi.org/10.48550/arXiv.2606.28457
arXiv-issued DOI via DataCite (pending registration)
Journal reference: Proceedings of CITALA 2014: 5th International Conference on Arabic Language Processing
Submission history
From: Diaa M. Fayed [view email] [v1] Fri, 26 Jun 2026 11:52:27 UTC (735 KB)
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