Maxenttagger for Malays Jawi POS-tags
Purpose - Malay is a major language of the Austronesian family spoken in many countries. Malay Jawi is lacking in annotated resources and tools. In addition, Part-of-speech (POS) ambiguity in Natural Language Processing (NLP) is a vague important phenomenon that needs to be solved immediately. Sinc...
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| Main Authors: | , , , |
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| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
2017
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| Subjects: | |
| Online Access: | http://repo.uum.edu.my/24498/1/SICONSEM%202017%2031%2033.pdf http://repo.uum.edu.my/24498/ |
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| Summary: | Purpose - Malay is a major language of the Austronesian family spoken in many countries. Malay Jawi is lacking in annotated resources and tools. In addition, Part-of-speech (POS) ambiguity in Natural Language Processing (NLP) is a vague important phenomenon that needs to be solved
immediately. Since POS is an important feature of the word, and is the link between the words and
syntax, POS tagging (POST) needs to provide intermediate results showing superior performance
to the next NLP tasks. POS ambiguity is a main problem in increasing POST performance. POST
performance is often measured with accuracy and precision of a tag and it was considered critical
to NLP application. Some of the standard package POS tagging provided in Natural Language
ToolKit (NLTK) are Brill tagger, HMM tagger, and CRF Tagger. In this paper, POST Malay Jawi
implemented NLP tools, NLTK for the state-of-the-art methods tagger; maximum entropy models.
NLTK is used as the implementation tool for Jawi tagging, as syntax and semantics of the language
is transparent, and it has the good functionality of NLP-operator. The tool also uses Python as the
implementation language. |
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