I3rab: A New Arabic Dependency Treebank Based on Arabic Grammatical Theory

TL;DR

This paper introduces I3rab, an Arabic dependency treebank based on traditional grammatical theory, which improves parser accuracy by up to 7.5% UAS and 18.8% LAS compared to existing resources.

Contribution

It presents a novel Arabic dependency treebank grounded in grammatical theory, enhancing parsing accuracy and addressing limitations of previous treebanks.

Findings

Up to 7.5% improvement in UAS

Up to 18.8% improvement in LAS

Better representation of pronouns and sentence structure

Abstract

Treebanks are valuable linguistic resources that include the syntactic structure of a language sentence in addition to POS-tags and morphological features. They are mainly utilized in modeling statistical parsers. Although the statistical natural language parser has recently become more accurate for languages such as English, those for the Arabic language still have low accuracy. The purpose of this paper is to construct a new Arabic dependency treebank based on the traditional Arabic grammatical theory and the characteristics of the Arabic language, to investigate their effects on the accuracy of statistical parsers. The proposed Arabic dependency treebank, called I3rab, contrasts with existing Arabic dependency treebanks in two main concepts. The first concept is the approach of determining the main word of the sentence, and the second concept is the representation of the joined and covert pronouns. To evaluate I3rab, we compared its performance against a subset of Prague Arabic Dependency Treebank that shares a comparable level of details. The conducted experiments show that the percentage improvement reached up to 7.5% in UAS and 18.8% in LAS.