Unsupervised Extraction of Verb Valency in Persian

Valency is the key concept in dependency grammar. Among different lexical categories, verbs play the most important role in syntax and semantics of the sentence in dependency grammar. Verbs are known to be the central point of sentences and reveal the main concept of the sentence. In this article, by investigating different methods of unsupervised Persian verb valence induction, we discuss specific issues in recognizing verbs in linguistics terms and ambiguities in Persian verb valence induction. We propose possible solutions for the mentioned challenges. According to our experiments, Expectation Maximization (EM) algorithm has the highest performance among all induction methods in Persian. We show that the performance of EM algorithm is more than twice as of the binomial hypothesis testing.