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ACL
2011

Pointwise Prediction for Robust, Adaptable Japanese Morphological Analysis

13 years 3 months ago
Pointwise Prediction for Robust, Adaptable Japanese Morphological Analysis
We present a pointwise approach to Japanese morphological analysis (MA) that ignores structure information during learning and tagging. Despite the lack of structure, it is able to outperform the current state-of-the-art structured approach for Japanese MA, and achieves accuracy similar to that of structured predictors using the same feature set. We also find that the method is both robust to outof-domain data, and can be easily adapted through the use of a combination of partial annotation and active learning.
Graham Neubig, Yosuke Nakata, Shinsuke Mori
Added 24 Aug 2011
Updated 24 Aug 2011
Type Journal
Year 2011
Where ACL
Authors Graham Neubig, Yosuke Nakata, Shinsuke Mori
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