Automatic labeling of semantic roles
Computational Linguistics
Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data
ICML '01 Proceedings of the Eighteenth International Conference on Machine Learning
Head-driven statistical models for natural language parsing
Head-driven statistical models for natural language parsing
EACL '99 Proceedings of the ninth conference on European chapter of the Association for Computational Linguistics
The Penn Chinese TreeBank: Phrase structure annotation of a large corpus
Natural Language Engineering
Chunking with support vector machines
NAACL '01 Proceedings of the second meeting of the North American Chapter of the Association for Computational Linguistics on Language technologies
Target word detection and semantic role chunking using support vector machines
NAACL-Short '03 Proceedings of the 2003 Conference of the North American Chapter of the Association for Computational Linguistics on Human Language Technology: companion volume of the Proceedings of HLT-NAACL 2003--short papers - Volume 2
Named entity extraction based on a maximum entropy model and transformation rules
ACL '00 Proceedings of the 38th Annual Meeting on Association for Computational Linguistics
Annotating the propositions in the Penn Chinese Treebank
SIGHAN '03 Proceedings of the second SIGHAN workshop on Chinese language processing - Volume 17
Question answering based on semantic structures
COLING '04 Proceedings of the 20th international conference on Computational Linguistics
Labeling chinese predicates with semantic roles
Computational Linguistics
Automatic semantic role labeling for Chinese verbs
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
An algorithm for semantic chunk identification of Chinese sentence
ISC '07 Proceedings of the 10th IASTED International Conference on Intelligent Systems and Control
Introduction to the CoNLL-2005 shared task: semantic role labeling
CONLL '05 Proceedings of the Ninth Conference on Computational Natural Language Learning
Semantics-driven shallow parsing for Chinese semantic role labeling
ACLShort '10 Proceedings of the ACL 2010 Conference Short Papers
Improving Chinese semantic role labeling with rich syntactic features
ACLShort '10 Proceedings of the ACL 2010 Conference Short Papers
Improving chinese event construction extraction with lexical relation pairs
NLDB'12 Proceedings of the 17th international conference on Applications of Natural Language Processing and Information Systems
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Recently, with the development of Chinese semantically annotated corpora, e.g. the Chinese Proposition Bank, the Chinese semantic role labeling (SRL) has been boosted. However, the Chinese SRL researchers now focus on the transplant of existing statistical machine learning methods which have been proven to be effective on English. In this paper, we have established a semantic chunking based method which is different from the traditional ones. Semantic chunking is named because of its similarity with syntactic chunking. The difference is that semantic chunking is used to identify the semantic chunks, i.e. the semantic roles. Based on semantic chunking, the process of SRL is changed from "parsing --- semantic role identification --- semantic role classification", to "semantic chunk identification --- semantic chunk classification". With the elimination of the parsing stage, the SRL task can get rid of the dependency on parsing, which is the bottleneck both of speed and precision. The experiments have shown that the semantic chunking based method outperforms previously best-reported results on Chinese SRL and saves a large amount of time.