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dc.contributor.advisor Dias G
dc.contributor.advisor Butt M
dc.contributor.author Sarveswaran K
dc.date.accessioned 2022
dc.date.available 2022
dc.date.issued 2022
dc.identifier.citation Sarveswaran, K. (2022). A Deep syntactic parser for the Tamil language [Doctoral dissertation, University of Moratuwa]. Institutional Repository University of Moratuwa. http://dl.lib.uom.lk/handle/123/21176
dc.identifier.uri http://dl.lib.uom.lk/handle/123/21176
dc.description.abstract Natural Language Processing (NLP) applications have become integral to human life. A syntactic parser is a vital linguistic tool that shows syntactic relations between the words in a sentence. These may then be mapped to a tree, a graph, or a formal structure. Syntactic parsers are helpful for building other NLP applications. In addition, they help linguists to understand a language better and perform cross-lingual linguistic analysis. A syntactic parser that performs a deeper analysis and captures argumentative, attributive and coordinative relations between the words of a given sentence is called a deep syntactic parser. Tamil is considered a low-resourced language in terms of tools, applications, and resources available for others to use and build NLP applications or carry out linguistic analyses. Not many resources, such as treebanks and annotated corpora, or linguistic analysis tools such as POS taggers or morphological analysers, are publicly available for Tamil. Available off-the-shelf language-agnostic syntactic parsers show comparatively low performance because of the rich morphosyntactic properties of Tamil. This study elaborates on how I developed the first grammar-driven parser for Tamil, which uses the Lexical-Functional Grammar formalism, and a state-of-the-art data-driven parser using the Universal Dependencies framework. I have also proposed an approach to evaluate a syntactic parser’s syntactical coverage, experimented with transition-based and graph-based approaches, and for the first time, tried multi-lingual training to develop a data-driven parser for Tamil. A part of speech tagger, a morphological analyser cum generator, pre-processing tools, and treebanks are the other tools and resources I have developed to facilitate the development of the parsers. While all these tools give the current best score for their respective tasks, these resources are also available online for others to build upon. Moreover, the study also documents my contributions toward understanding different linguistic aspects of the Tamil language. en_US
dc.language.iso en en_US
dc.subject DEEP SYNTACTIC PARSER en_US
dc.subject MORPHOLOGICAL ANALYSE en_US
dc.subject GRAMMAR-DRIVEN PARSER en_US
dc.subject DATA-DRIVEN PARSER en_US
dc.subject PART OF SPEECH TAGGER en_US
dc.subject INFORMATION TECHNOLOGY -Dissertation en_US
dc.subject COMPUTER SCIENCE -Dissertation en_US
dc.title A Deep syntactic parser for the Tamil language en_US
dc.type Thesis-Abstract en_US
dc.identifier.faculty Engineering en_US
dc.identifier.degree Doctor of Philosophy en_US
dc.identifier.department Department of Computer Science and Engineering en_US
dc.date.accept 2022
dc.identifier.accno TH5064 en_US


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