Authors: Shubhnandan S. Jamwal; Parul Gupta; Vijay Singh Sen
Addresses: Department of Computer Science and IT, University of Jammu, J&K, 180006, India ' Department of Computer Science and IT, University of Jammu, J&K, 180006, India ' Department of Computer Science and IT, University of Jammu, J&K, 180006, India
Abstract: Morphological analyser, POS data, Stemmer etc. are the basic tools required for any NLP tasks, which are not available for Dogri language which recently has been declared as an official language of J&K, UT. Because of the unavailability of the basic tools, it remains a very low resourced language. In this paper, we have presented a sub task for the development of morphological analyser for Dogri language. We have identified the morphological behaviour of the verbs and implemented the automatic process of the identification of the verbs in Dogri language using paradigm approach. The various forms of verb taken into consideration are specifically transitive, intransitive, non-finite, gerund and infinitives. The average accuracy attained in the process of identification of transitive, intransitive, non-finite, gerund and infinitive verbs is 80%, 83%, 76%, 93%, 88% respectively.
Keywords: morphology; Dogri; inflections; paradigm; verb; non-finite; gerund; transitive; intransitive; stemming; verb detection; low resource language; computational linguistics; supervised identification; verb classification; algorithms; tokenisation; morphological analysis.
International Journal of Intelligent Engineering Informatics, 2021 Vol.9 No.4, pp.412 - 423
Received: 01 Nov 2020
Accepted: 23 Jul 2021
Published online: 06 Jan 2022 *