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A Maximum Entropy Approach to Kannada Part Of Speech Tagging

by Shambhavi.b. R, Ramakanth Kumar P, Revanth G
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 41 - Number 13
Year of Publication: 2012
Authors: Shambhavi.b. R, Ramakanth Kumar P, Revanth G
10.5120/5600-7852

Shambhavi.b. R, Ramakanth Kumar P, Revanth G . A Maximum Entropy Approach to Kannada Part Of Speech Tagging. International Journal of Computer Applications. 41, 13 ( March 2012), 9-12. DOI=10.5120/5600-7852

@article{ 10.5120/5600-7852,
author = { Shambhavi.b. R, Ramakanth Kumar P, Revanth G },
title = { A Maximum Entropy Approach to Kannada Part Of Speech Tagging },
journal = { International Journal of Computer Applications },
issue_date = { March 2012 },
volume = { 41 },
number = { 13 },
month = { March },
year = { 2012 },
issn = { 0975-8887 },
pages = { 9-12 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume41/number13/5600-7852/ },
doi = { 10.5120/5600-7852 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:29:30.079406+05:30
%A Shambhavi.b. R
%A Ramakanth Kumar P
%A Revanth G
%T A Maximum Entropy Approach to Kannada Part Of Speech Tagging
%J International Journal of Computer Applications
%@ 0975-8887
%V 41
%N 13
%P 9-12
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Part Of Speech (POS) tagging is the most important pre-processing step in almost all Natural Language Processing (NLP) applications. It is defined as the process of classifying each word in a text with its appropriate part of speech. In this paper, the probabilistic classifier technique of Maximum Entropy model is experimented for the tagging of Kannada sentences. Kannada language is agglutinative, morphologically very rich but resource poor. Hence 51267 words from EMILLE corpus were manually tagged and used as training data. The tagset included 25 tags as defined for Indian languages. The best suited feature set for the language was finalised after rigorous experiments. Data size of 2892 word forms was downloaded from Kannada websites for testing. Accuracy of 81. 6% was obtained in the experiments which prove that Maximum Entropy is well suited for Kannada language.

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Index Terms

Computer Science
Information Sciences

Keywords

Natural Language Processing Part Of Speech Tagging Maximum Entropy

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