Head-driven statistical models for natural language parsing
Head-driven statistical models for natural language parsing
Accessor variety criteria for Chinese word extraction
Computational Linguistics
The first international Chinese word segmentation Bakeoff
SIGHAN '03 Proceedings of the second SIGHAN workshop on Chinese language processing - Volume 17
A maximum entropy Chinese character-based parser
EMNLP '03 Proceedings of the 2003 conference on Empirical methods in natural language processing
Pseudo-projective dependency parsing
ACL '05 Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics
Chinese segmentation and new word detection using conditional random fields
COLING '04 Proceedings of the 20th international conference on Computational Linguistics
Parsing syntactic and semantic dependencies with two single-stage maximum entropy models
CoNLL '08 Proceedings of the Twelfth Conference on Computational Natural Language Learning
Long distance dependency in language modeling: an empirical study
IJCNLP'04 Proceedings of the First international joint conference on Natural Language Processing
Cross language dependency parsing using a bilingual lexicon
ACL '09 Proceedings of the Joint Conference of the 47th Annual Meeting of the ACL and the 4th International Joint Conference on Natural Language Processing of the AFNLP: Volume 1 - Volume 1
Parsing the internal structure of words: a new paradigm for Chinese word segmentation
HLT '11 Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies - Volume 1
A new unsupervised approach to word segmentation
Computational Linguistics
Unified dependency parsing of Chinese morphological and syntactic structures
EMNLP-CoNLL '12 Proceedings of the 2012 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning
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We investigate the possibility of exploiting character-based dependency for Chinese information processing. As Chinese text is made up of character sequences rather than word sequences, word in Chinese is not so natural a concept as in English, nor is word easy to be defined without argument for such a language. Therefore we propose a character-level dependency scheme to represent primary linguistic relationships within a Chinese sentence. The usefulness of character dependencies are verified through two specialized dependency parsing tasks. The first is to handle trivial character dependencies that are equally transformed from traditional word boundaries. The second furthermore considers the case that annotated internal character dependencies inside a word are involved. Both of these results from character-level dependency parsing are positive. This study provides an alternative way to formularize basic character-and word-level representation for Chinese.