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International Journal of

Recent Trends in Engineering

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International Journal of Recent Trends in Engineering (IJRTE)

ISSN 1797-9617

Volume 1, Number 1, May 2009

Issue on Computer Science

Page(s): 483-489

Semantic Role Labeling for Tamil Documents

S. Lakshmana Pandian, T.V. Geetha

Full text: PDF

Abstract

The aim of this work is to design and implement a system to identify, analyze and tag the constituents in the sentence which fill a semantic role expressed by some target verbs of a sentence in Tamil. The system reads a Tamil text document and performs tagging of semantic roles associated with a given target verb such as Agent, Patient, Instrument, etc. and also adjuncts such as Locative, Temporal, Manner, Cause, etc. within such a document using a hybrid approach by considering syntactic, semantic, and statistical evidence in the sentences. It consists of two main phases-a Learning Phase and an Evaluation Phase. The Learning phase consists of two main components namely a Maximum Entropy Model (MEM) and a Learning Component. The Evaluation Phase consists of four main components namely MEM Evaluator, Verb Frame Invoker, Rule Based Probability Assigner and Expectation Maximizer Component. A number of different performance measures are charted and the performance of the system is judged on the criteria of accuracy, ambiguity in labeling and how the labeling was performed.

Index Terms

semantic role, Maximum entropy model, expectation-maximization

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