Automatic Verb Detection in Libyan dialect

Abstract

Automatic recognition of verbs is crucial to a wide range of natural language processing tasks. Verbs exhibit the relational information in a sentence between the action and its participant and are considered the primary source of information in understanding a sentence and the base for any NLP task. In this paper, we experiment six machine learning algorithms to identify verbs from other words in the Libyan dialect. Among algorithms used, the Support vector classifier (SVC) was best at identifying verbs with a micro F1 score of 70%.