Work

Semi-Automatic Data Annotation, POS Tagging and Mildly Context-Sensitive Disambiguation: The eXtended Revised AraMorph (XRAM)

Year: 2018

Type: book-chapter

Abstract: An extended, revised form of Tim Buckwalter's Arabic lexical and morphological resource AraMorph, eXtended Revised AraMorph (henceforth XRAM), is presented which addresses a number of weaknesses and inconsistencies of the original model by allowing a wider coverage of real-world Classical and contemporary (both formal and informal) Arabic texts. Building upon previous research, XRAM enhancements include (i) flag-selectable usage markers, (ii) probabilistic mildly context-sensitive POS tagging, filtering, disambiguation and ranking of alternative morphological analyses, (iii) semi-automatic increment of lexical coverage through extraction of lexical and morphological information from existing lexical resources. Testing of XRAM through a front-end Python module showed a remarkable success level.

Source: WORLD SCIENTIFIC eBooks

DOI: 10.1142/9789813229396_0007

Authors: Giuliano Lancioni, Laura Garofalo, Raoul Villano, Francesca Romana Romani, Marta Campanelli, Ilaria Cicola, Ivana Pepe, Valeria Pettinari, Simona Olivieri

Institutions: Roma Tre University, Sapienza University of Rome, University of Helsinki

Language: English

Topic: Natural Language Processing Techniques

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

OpenAlex ID: W2295852458

FWCI:

Cites: 3

Cited by: 1

Related to: 10