A Word Sense Disambiguation Technique for Sinhala

Arukgoda, Janindu; Bandara, Vidudaya; Bashani, Samiththa; Gamage, Vijayindu; Wimalasuriya, Daya C.

doi:10.1109/icaiet.2014.42

Cited by 5 publications

(2 citation statements)

References 4 publications

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“…There have been multiple attempts to do word sense disambiguation (WSD) [140][141][142][143][144] for Sinhala. For this, Arukgoda et al [145] have proposed a system based on the Lesk Algorithm [146] while Marasinghe et al [147] have proposed a system based on probabilistic modeling. A dialogue act recognition system which utilizes simple classification algorithms has been proposed by Palihakkara et al [148].…”

Section: Semantic Toolsmentioning

confidence: 99%

Survey on Publicly Available Sinhala Natural Language Processing Tools and Research

Silva¹

2019

Preprint

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Sinhala is the native language of the Sinhalese people who make up the largest ethnic group of Sri Lanka. The language belongs to the globe-spanning language tree, Indo-European. However, due to poverty in both linguistic and economic capital, Sinhala, in the perspective of Natural Language Processing tools and research, remains a resource-poor language which has neither the economic drive its cousin English has nor the sheer push of the law of numbers a language such as Chinese has. A number of research groups from Sri Lanka have noticed this dearth and the resultant dire need for proper tools and research for Sinhala natural language processing. However, due to various reasons, these attempts seem to lack coordination and awareness of each other. The objective of this paper is to fill that gap of a comprehensive literature survey of the publicly available Sinhala natural language tools and research so that the researchers working in this field can better utilize contributions of their peers. As such, we shall be uploading this paper to arXiv and perpetually update it periodically to reflect the advances made in the field.

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Section: Semantic Toolsmentioning

confidence: 99%

Survey on Publicly Available Sinhala Natural Language Processing Tools and Research

Silva¹

2019

Preprint

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“…Prior to this work on Sinhala Language, previous study was carried out by A. Marasinghe, S. Herath, and A. Herath [19].They proposed a method to disambiguate Sinhala words based on an unsupervised leaning technique with the use of Susantha-Corpus [19].The two unsupervised learning methods -EM algorithm and Gibbs sampling were used to show the result of disambiguation of five words. The system could only disambiguate up to 5 nouns as the number of ambiguous target words used in this study was very small.…”

Section: Sinhalamentioning

confidence: 99%

Techniques for Disambiguation of Polysemy Words: A Review

Singh¹,

Kr.²

2019

IJCA

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The domain of Computational Linguistics involves the key task of Word Sense Disambiguation which aims to assign a meaning to particular word in terms of the context with which it is used in a sentence. The task of assigning the semantically correct meaning to a polysemy word in almost all the languages of the world stands out to be an open problem of research with considerably low accuracies achieved. The paper presents a meticulous review of the various techniques opted for disambiguation of polysemy words in various languages-English, Hindi, Nepalese, Tamil, Kannada, Telugu, Malayalam, Sinhala and German. Also, an insight into how the various approaches-supervised (involving corpora) and Unsupervised (clustering, meta thesaurus) to solving the above problems evolved over the years to get the accuracy improved. The applications include word processing, spell checking, content analysis, translation, improved search engines.

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