A Computational Approach to Grammatical Coding of English Words
Journal of the ACM (JACM)
Building a large annotated corpus of English: the penn treebank
Computational Linguistics - Special issue on using large corpora: II
Coping with ambiguity and unknown words through probabilistic models
Computational Linguistics - Special issue on using large corpora: II
Tagging English text with a probabilistic model
Computational Linguistics
TnT: a statistical part-of-speech tagger
ANLC '00 Proceedings of the sixth conference on Applied natural language processing
A simple rule-based part of speech tagger
ANLC '92 Proceedings of the third conference on Applied natural language processing
Comparison of alignment templates and maximum entropy models for natural language understanding
EACL '03 Proceedings of the tenth conference on European chapter of the Association for Computational Linguistics - Volume 1
Statistical phrase-based translation
NAACL '03 Proceedings of the 2003 Conference of the North American Chapter of the Association for Computational Linguistics on Human Language Technology - Volume 1
Adding morphological information to a connectionist part-of-speech tagger
CAEPIA'09 Proceedings of the Current topics in artificial intelligence, and 13th conference on Spanish association for artificial intelligence
SLSP'13 Proceedings of the First international conference on Statistical Language and Speech Processing
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In this paper, a new approach to the Part-of-Speech (PoS) tagging problem is proposed. The PoS tagging problem can be viewed as a special translation process where the source language is the set of strings being considered and the target language is the sequence of POS tags. In this work, we have used phrase-based machine translation technology to tackle the PoS tagging problem. Experiments on the Penn Treebank WSJ task were carried out and very good results were obtained.