Automatic Part-of-Speech Tagging of Arabic-English Dictionary Senses through WordNet

• URL: http://arxiv.org/abs/2606.24359v1
• Date: Tue, 23 Jun 2026 09:49:26 GMT
• Title: Automatic Part-of-Speech Tagging of Arabic-English Dictionary Senses through WordNet
• Abstract summary: This paper proposed an algorithm for part-of-speech (POS) tagging senses of a bilingual dictionary.<n>The algorithm is applied on the Al-Mawrid Arabic-English dictionary.
• Score: 0.4374837991804084
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: This paper proposed an algorithm for part-of-speech (POS) tagging senses of a bilingual dictionary. The algorithm is applied on the Al-Mawrid Arabic-English dictionary. The tagging task is accomplished by transferring the POS tags of the English translation equivalences (TEs) to the dictionary senses after dis-ambiguities process. The English POS tags of senses are acquired from the Princeton WordNet. POS tagging of bilingual dictionary senses is prerequisite to link a bilingual dictionary to WordNet and/or standardizing that dictionary into WordNet-LMF format where the synset (set of synonyms), not word, is the basic brick. The registered accuracy is high though the cost is little. Building NLP/HLT tools needs linguistic experts, large investments, and long time. For statistical approach, we need large annotated corpora and for rule-based approach, we need large lexicon that contains rich linguistic and world knowledge. That motivates the appearance of what are called resource-light approaches to develop natural language processing (NLP) tools for poor-resource languages.

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