Improving wordnets for under-resourced languages using machine translation
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Date
2018-01-08Author
Chakravarthi, Bharathi Raja
Arcan, Mihael
McCrae, John P.
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Chakravarthi, Bharathi Raja, Arcan, Mihael, & McCrae, John P. (2018). Improving wordnets for under-resourced languages using machine translation. Paper presented at the GWC 2018, The 9th Global WordNet Conference, Nanyang Technological University (NTU), Singapore, 8 – 12 January.
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Abstract
Wordnets are extensively used in natural
language processing, but the current approaches for manually building a wordnet from scratch involves large research
groups for a long period of time, which are
typically not available for under-resourced
languages. Even if wordnet-like resources
are available for under-resourced languages, they are often not easily accessible, which can alter the results of applications using these resources. Our proposed
method presents an expand approach for
improving and generating wordnets with
the help of machine translation. We apply our methods to improve and extend
wordnets for the Dravidian languages, i.e.,
Tamil, Telugu, Kannada, which are severly under-resourced languages. We report
evaluation results of the generated wordnet senses in term of precision for these
languages. In addition to that, we carried
out a manual evaluation of the translations
for the Tamil language, where we demonstrate that our approach can aid in improving wordnet resources for under-resourced
Dravidian languages.