Extended Models and Tools for High-performance Part-of-speech

  title={Extended Models and Tools for High-performance Part-of-speech},
  author={Masayuki Asahara and Yuji Matsumoto},
Statistical part-of-speech(POS) taggers achieve high accuracy and robustness when based on large scale manually tagged corpora. However, enhancements of the learning models are necessary to achieve better performance. We are developing a learning tool for a Japanese morphological analyzer called ChaSen. Currently we use a ne-grained POS tag set with about 500 tags. To apply a normal trigram model on the tag set, we need unrealistic size of corpora. Even, for a bi-gram model, we cannot prepare a… CONTINUE READING
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1 Excerpt

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