Abhilash Inumella

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We describe two systems that participated in SemEval-2010 task 17 (All-words Word Sense Disambiguation on a Specific Domain) and were ranked in the third and fourth positions in the formal evaluation. Domain adaptation techniques using the background documents released in the task were used to assign ranking scores to the words and their senses. The test(More)
In the task of semantic category labeling, given a text, every word in it has to be assigned a semantic category. Our language of interest is Hindi. We use the ontological categories defined in Hindi Wordnet as semantic category inventories. In this paper we present two unsupervised approaches namely Flat Semantic Category Labeler (FSCL) and Hierarchical(More)
Hindi is an Indian language which is relatively rich in morphology. A few morphological analyzers of this language have been developed. However, they give only inflectional analysis of the language. In this paper, we present our Hindi derivational morphological analyzer. Our algorithm upgrades an existing inflectional analyzer to a derivational analyzer and(More)
One of the important phase of Natural language Processing is Morphological Analysis that helps in work of machine translation. Effective implementation of morphological analyzer can be seen in language which is rich in morphemes. Hindi being an inflected language has capability of generating hundreds of words from the root word. It is morphologically rich(More)
Most tools and resources developed for natural language processing of Arabic are designed for Modern Standard Arabic (MSA) and perform terribly on Arabic dialects, such as Egyptian Arabic. Egyptian Arabic differs from MSA phonologically, morphologically and lexically and has no standardized orthography. We present a linguistically accurate, large-scale(More)
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