DocumentCode :
3288944
Title :
MATAr: Morphology-based Tagger for Arabic
Author :
Zaraket, Fadi A. ; Jaber, Ali
Author_Institution :
Dept. of Electr. & Comput. Eng., American Univ. of Beirut, Beirut, Lebanon
fYear :
2013
fDate :
27-30 May 2013
Firstpage :
1
Lastpage :
4
Abstract :
Computational linguistic and natural language processing automation tasks require text annotated with tags that represent the desired output of the task. The annotation tags serve for training, validation, and evaluation. Arabic morphological analysis, and tags associated with it such as part of speech and gloss tags, is key to Arabic computational linguistics and natural language processing. Several manual and automated tagging tools exist for text. Very few exist that are based on Arabic morphological analysis. In this paper, we present an open source tagging tool with visual interface that enables the construction of annotated Arabic text corpora with automatic morphology-based tags. The tool allows the specification of tags with Boolean formulae where the atomic predicates are match and contain relations between the morphological solution of part of the text and the value of a morphological feature. The tool allows the user to directly enter manual tags, to edit existing tags through a tag sensitive coloring interface, to compare tag sets, and compute accuracy results.
Keywords :
Boolean algebra; computational linguistics; feature extraction; natural language processing; public domain software; text analysis; user interfaces; Arabic computational linguistics; Arabic morphological analysis; Boolean formulae; MATAR; annotated Arabic text corpora construction; annotation tags; atomic predicate matching; automated tagging tools; automatic morphology-based tags; contain relations; manual tags; morphological feature; morphological solution; morphology-based tagger for Arabic; natural language processing; open source tagging tool; tag editing; tag sensitive coloring interface; tag sets; tag specification; visual interface; Accuracy; Computational linguistics; Morphology; Semantics; Tagging; Vectors; Visualization; Arabic; Computational linguistics; Morphological analysis; Natural language processing; Tagging;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Systems and Applications (AICCSA), 2013 ACS International Conference on
Conference_Location :
Ifrane
ISSN :
2161-5322
Type :
conf
DOI :
10.1109/AICCSA.2013.6616418
Filename :
6616418
Link To Document :
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