Work

Arabic Tweets Treebanking and Parsing: A Bootstrapping Approach

Year: 2017

Type: conference-paper

Abstract: In this paper, we propose using a "bootstrapping" method for constructing a dependency treebank of Arabic tweets.This method uses a rule-based parser to create a small treebank of one thousand Arabic tweets and a data-driven parser to create a larger treebank by using the small treebank as a seed training set.We are able to create a dependency treebank from unlabelled tweets without any manual intervention.Experiments results show that this method can improve the speed of training the parser and the accuracy of the resulting parsers.

Source: Arabic Natural Language Processing Workshop (WANLP)

DOI: 10.18653/v1/w17-1312

Authors: Fahad Albogamy, Allan Ramsay, Hanady Ahmed

Institutions: University of Manchester, Qatar University

Language: English

Topic: Natural Language Processing Techniques

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: hybrid

Funders: Qatar Foundation, Fonds National de la Recherche Luxembourg, King Saud University, Qatar National Research Fund

Award: G3362826306