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Erschienen in:
2015 | OriginalPaper | Buchkapitel
High Quality Arabic Lexical Ontology Based on MUHIT, WordNet, SUMO and DBpedia
verfasst von : Eslam Kamal, Mohsen Rashwan, Sameh Alansary
Erschienen in: Computational Linguistics and Intelligent Text Processing
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In this paper, we aim to move ontology-based Arabic NLP forward by experimenting with the generation of a comprehensive Arabic lexical ontology using multiple language resources. We recommend a combination of MUHIT, WordNet and SUMO and use a simple method to link them, which results in the generation of an Arabic-lexicalized version of the SUMO ontology. Then, we evaluate the generated ontology, and propose a method for increasing its named entity coverage using DBpedia, English-to-Arabic Transliteration, and Named Entity Recognition. We end up with an Arabic lexical ontology that has 228K Arabic synsets, linked to 7.8K concepts and 143K instances. This ontology achieves a precision of 96.9% and recall of 75.5% for NLU scenarios.