LDC Arabic Treebanks and Associated Corpora: Data Divisions Manual

TL;DR

This paper presents a set of standardized rules for dividing Arabic treebank corpora into training, development, and test sets to ensure consistency across NLP research and applications.

Contribution

It introduces a systematic methodology for dividing Arabic treebank data, facilitating consistent and reproducible NLP experiments and model evaluations.

Findings

Established division rules for Arabic treebanks

Enhanced consistency in NLP research datasets

Supported reliable model training and evaluation

Abstract

The Linguistic Data Consortium (LDC) has developed hundreds of data corpora for natural language processing (NLP) research. Among these are a number of annotated treebank corpora for Arabic. Typically, these corpora consist of a single collection of annotated documents. NLP research, however, usually requires multiple data sets for the purposes of training models, developing techniques, and final evaluation. Therefore it becomes necessary to divide the corpora used into the required data sets (divisions). This document details a set of rules that have been defined to enable consistent divisions for old and new Arabic treebanks (ATB) and related corpora.