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arXiv · 1603.01833

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

Giuliano Lancioni·Valeria Pettinari·Laura Garofalo·Marta Campanelli·Ivana Pepe·Simona Olivieri·Ilaria Cicola
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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.

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Giuliano Lancioni, Valeria Pettinari, Laura Garofalo, Marta Campanelli, Ivana Pepe, Simona Olivieri, Ilaria Cicola. 2016-03-06. Semi-Automatic Data Annotation, POS Tagging and Mildly Context-Sensitive Disambiguation: the eXtended Revised AraMorph (XRAM). https://arxiv.org/abs/1603.01833

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