A novel approach for identification and classification of verbs in Dogri language. (6th January 2022) - Jamwal, Shubhnandan S.; Gupta, Parul; Sen, Vijay Singh
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.