| C00-2119 | information alone can resolve most | word-breaking | ambiguities . Nonetheless , some |
| W12-2106 | using the Microsoft Data-Driven | Word-Breaking | API3 . This also benefits the |
| C00-2119 | annotating corpora for target | word-breaking | and POS tagging . We also thank |
| W02-1604 | features owing to the need for | word-breaking | in Japanese ( Suzuki et al. 2000 |
| C00-2119 | Using a Broad-Coverage Parser for | Word-Breaking | in Japanese </title> Hisami Suzuki |
| C00-2119 | achieve high accuracy in POS-labeled | word-breaking | . Separating the tasks of word |
| C00-2119 | over a wide varicty of data . | Word-breaking | accuracy of our system is currently |
| W04-1119 | APIs ) . MSWS first conducts the | word-breaking | using MM ( aug - mented by heuristic |
| C00-2119 | identification of words ( in the | word-breaking | component ) and the selection |
| C00-2119 | implemented without requiring the | word-breaking | component to return a single |
| C00-2119 | two parses corresponding to two | word-breaking | analyses , of which the first |
| W11-1505 | punctuation into various classes ( e.g. | word-breaking | vs. non-breaking ) and also uses |
