A Sense Annotated Corpus for All-Words Urdu Word Sense Disambiguation

Saeed, Ali and Nawab, Rao Muhammad Adeel and Stevenson, Mark and Rayson, Paul Edward (2019) A Sense Annotated Corpus for All-Words Urdu Word Sense Disambiguation. ACM Transactions on Asian and Low-Resource Language Information Processing (TALLIP), 18 (4). ISSN 2375-4699

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Abstract

Word Sense Disambiguation (WSD) aims to automatically predict the correct sense of a word used in a given context. All human languages exhibit word sense ambiguity, and resolving this ambiguity can be difficult. Standard benchmark resources are required to develop, compare, and evaluate WSD techniques. These are available for many languages, but not for Urdu, despite this being a language with more than 300 million speakers and large volumes of text available digitally. To fill this gap, this study proposes a novel benchmark corpus for the Urdu All-Words WSD task. The corpus contains 5,042 words of Urdu running text in which all ambiguous words (856 instances) are manually tagged with senses from the Urdu Lughat dictionary. A range of baseline WSD models based on n-gram are applied to the corpus, and the best performance (accuracy of 57.71%) is achieved using word 4-gram. The corpus is freely available to the research community to encourage further WSD research in Urdu.

Item Type:
Journal Article
Journal or Publication Title:
ACM Transactions on Asian and Low-Resource Language Information Processing (TALLIP)
ID Code:
132779
Deposited By:
Deposited On:
15 Apr 2019 10:50
Refereed?:
Yes
Published?:
Published
Last Modified:
27 Mar 2020 04:15