A Hybrid Algorithm for Recognizing the Position of Ezafe Constructions in Persian Texts

Abstract

 Abtract-In the Persian language, an Ezafe construction is a linking element which joins the head of a phrase to its modifiers. The Ezafe in its simplest form is pronounced as-e, but generally not indicated in writing. Determining the position of an Ezafe is advantageous for disambiguating the boundary of the syntactic phrases which is a fundamental task in most natural language processing applications. This paper introduces a framework for combining genetic algorithms with rule-based models that brings the advantages of both approaches and overcomes their problems. This framework was used for recognizing the position of Ezafe constructions in Persian written texts. At the first stage, the rulebased model was applied to tag some tokens of an input sentence. Then, in the second stage, the search capabilities of the genetic algorithm were used to assign the Ezafe tag to untagged tokens using the previously captured training information. The proposed framework was evaluated on Peykareh corpus and it achieved 95.26 percent accuracy. Test results show that this proposed approach outperformed other approaches for recognizing the position of Ezafe constructions.

Persian Ezafe Recognition Using Transformers and Its Role in Part-Of-Speech Tagging

“…The obtained accuracy is 93.29%, reportedly. Another work is Noferesti and Shamsfard (2014) that uses both a rule-based method and a genetic algorithm. At first, they apply 53 syntactic, morphological, and lexical rules to texts to determine words with ezafe.…”

IJIMAI Editor's Note - Vol. 2 Issue 6

“…The proposed framework was evaluated on Peykareh corpus and it achieved 95.26 percent accuracy. Test results show that this proposed approach outperformed other approaches for recognizing the position of Ezafe constructions [2].…”

On the Importance of Ezafe Construction in Persian Parsing

“…There are few studies (Noferesti and Shamsfard, 2014;Asghari et al, 2014) on automatically finding Ezafe construction. In this work, we modify the part of speech tagset for the Persian words.…”