8 search results - page 1 / 2 » Using a Smoothing Maximum Entropy Model for Chinese Nominal ... |
IJCNLP
2004
Springer
13 years 10 months ago
2004
Springer
This paper treats nominal entity tagging as a six-way (five categories plus nonentity) classification problem and applies a smoothing maximum entropy (ME) model with a Gaussian pr...
EMNLP
2004
13 years 6 months ago
2004
Traditional word alignment approaches cannot come up with satisfactory results for Named Entities. In this paper, we propose a novel approach using a maximum entropy model for nam...
IJCNLP
2004
Springer
13 years 10 months ago
2004
Springer
In this paper, we present a deterministic dependency structure analyzer for Chinese. This analyzer implements two algorithms – Yamada and Nivre models – and two sorts of class...
CORR
2000
Springer
13 years 4 months ago
2000
Springer
Trigrams'n'Tags (TnT) is an efficient statistical part-of-speech tagger. Contrary to claims found elsewhere in the literature, we argue that a tagger based on Markov mod...
ANLP
2000
13 years 6 months ago
2000
Trigrams'n'Tags (TnT) is an efficient statistical part-of-speech tagger. Contrary to claims found elsewhere in the literature, we argue that a tagger based on Markov mod...