A Hybrid Model for Part-of-Speech Tagging and its Application to Bengali
نویسندگان
چکیده
— This paper describes our work on Bengali Part of Speech (POS) tagging using a corpus-based approach. There are several approaches for part of speech tagging. This paper deals with a model that uses a combination of supervised and unsupervised learning using a Hidden Markov Model (HMM). We make use of small tagged corpus and a large untagged corpus. We also make use of Morphological Analyzer. Bengali is a highly ambiguous and relatively free word order language. We have obtained an overall accuracy of 95%. Keywords—About four key words or phrases in alphabetical order, separated by commas.
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