Titlebook: Computational Linguistics and Intelligent Text Processing; 16th International C Alexander Gelbukh Conference proceedings 2015 Springer Inte

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High Quality Arabic Lexical Ontology Based on MUHIT, WordNet, SUMO and DBpediaty 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.

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Data-Driven Morphological Analysis and Disambiguation for Kazakhg our method against open source solutions on several data sets, we show that it achieves better or on par performance. We also provide an extensive error analysis that sheds light on common problems of the morphological disambiguation of the language.

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