A Deep Level Tagger for Malayalam, a Morphologically Rich Language
In recent years, there has been tremendous growth in the amount of natural language text through various sources. Computational analysis of this text has got considerable attention among the NLP researchers. Automatic analysis and representation of natural language text is a step by step procedure....
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| Auteurs principaux: | , , , |
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| Format: | article |
| Langue: | EN |
| Publié: |
De Gruyter
2020
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| Sujets: | |
| Accès en ligne: | https://doaj.org/article/f61e744ccf2e40b39a6d767b95fb0e60 |
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| Résumé: | In recent years, there has been tremendous growth in the amount of natural language text through various sources. Computational analysis of this text has got considerable attention among the NLP researchers. Automatic analysis and representation of natural language text is a step by step procedure. Deep level tagging is one of such steps applied over the text. In this paper, we demonstrate a methodology for deep level tagging of Malayalam text. Deep level tagging is the process of assigning deeper level information to every noun and verb in the text along with normal POS tags. In this study, we move towards a direction that is not much explored in the case of Malayalam language. Malayalam is a morphologically rich and agglutinative language. The morphological features of the language are effectively utilized for the computational analysis of Malayalam text. The language level details required for the study are provided by Thunjath Ezhuthachan Malayalam University, Tirur. |
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