A word sense disambiguation corpus for Urdu

Saeed, Ali and Nawab, Rao Muhammad Adeel and Stevenson, Mark and Rayson, Paul (2019) A word sense disambiguation corpus for Urdu. Language Resources and Evaluation, 53 (3). 397–418. ISSN 1574-020X

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The aim of word sense disambiguation (WSD) is to correctly identify the meaning of a word in context. All natural languages exhibit word sense ambiguities and these are often hard to resolve automatically. Consequently WSD is considered an important problem in natural language processing (NLP). Standard evaluation resources are needed to develop, evaluate and compare WSD methods. A range of initiatives have lead to the development of benchmark WSD corpora for a wide range of languages from various language families. However, there is a lack of benchmark WSD corpora for South Asian languages including Urdu, despite there being over 300 million Urdu speakers and a large amounts of Urdu digital text available online. To address that gap, this study describes a novel benchmark corpus for the Urdu Lexical Sample WSD task. This corpus contains 50 target words (30 nouns, 11 adjectives, and 9 verbs). A standard, manually crafted dictionary called Urdu Lughat is used as a sense inventory. Four baseline WSD approaches were applied to the corpus. The results show that the best performance was obtained using a simple Bag of Words approach. To encourage NLP research on the Urdu language the corpus is freely available to the research community.

Item Type:
Journal Article
Journal or Publication Title:
Language Resources and Evaluation
Additional Information:
The final publication is available at Springer via http://dx.doi.org/10.1007/s10579-018-9438-7
Uncontrolled Keywords:
?? lexical sample tasksense tagged urdu corpusword sense disambiguationlanguage and linguisticseducationlinguistics and languagelibrary and information sciences ??
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Deposited On:
22 Jun 2019 08:52
Last Modified:
11 Jan 2024 00:20