TnT: a statistical part-of-speech tagger
ANLC '00 Proceedings of the sixth conference on Applied natural language processing
Development of a POS Tagger for Malayalam - An Experience
ARTCOM '09 Proceedings of the 2009 International Conference on Advances in Recent Technologies in Communication and Computing
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Subject and object identification denotes the process of identifying the syntactic subject and object in a sentence while tagging. Identification of subject/object turned out as very effective for many natural language applications such as machine translation, anaphora resolution, relationship extraction etc. For languages with rigid word order, the subject, object and verb in a sentence can be identified by their position. But for languages like Malayalam with relatively free word order the subject/object identification task is more complex and is significant. This paper presents a method for subject and object identification in Malayalam text using statistical tagging approach using HMM and Viterbi algorithm. In this approach, the tagset for part of speech tagging is modified to include tags that distinguish between the subject and object in a sentence.