A maximum entropy approach to natural language processing
Computational Linguistics
Automatic labeling of semantic roles
Computational Linguistics
The FrameNet tagset for frame-semantic and syntactic coding of predicate-argument structure
NAACL 2000 Proceedings of the 1st North American chapter of the Association for Computational Linguistics conference
Sinica Treebank: design criteria, annotation guidelines, and on-line interface
CLPW '00 Proceedings of the second workshop on Chinese language processing: held in conjunction with the 38th Annual Meeting of the Association for Computational Linguistics - Volume 12
Annotating information structures in Chinese texts using HowNet
CLPW '00 Proceedings of the second workshop on Chinese language processing: held in conjunction with the 38th Annual Meeting of the Association for Computational Linguistics - Volume 12
Annotating the propositions in the Penn Chinese Treebank
SIGHAN '03 Proceedings of the second SIGHAN workshop on Chinese language processing - Volume 17
Building a large Chinese corpus annotated with semantic dependency
SIGHAN '03 Proceedings of the second SIGHAN workshop on Chinese language processing - Volume 17
Identifying semantic roles using Combinatory Categorial Grammar
EMNLP '03 Proceedings of the 2003 conference on Empirical methods in natural language processing
The Proposition Bank: An Annotated Corpus of Semantic Roles
Computational Linguistics
Joint learning improves semantic role labeling
ACL '05 Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics
Models for the semantic classification of noun phrases
CLS '04 Proceedings of the HLT-NAACL Workshop on Computational Lexical Semantics
Dependency-based statistical machine translation
ACLstudent '05 Proceedings of the ACL Student Research Workshop
Automatic semantic role labeling for Chinese verbs
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
Question answering for dutch using dependency relations
CLEF'05 Proceedings of the 6th international conference on Cross-Language Evalution Forum: accessing Multilingual Information Repositories
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Semantic analysis is a standard tool in the Natural Language Processing (NLP) toolbox with widespread applications. In this article, we look at tagging part of the Penn Chinese Treebank with semantic dependency. Then we take this tagged data to train a maximum entropy classifier to label the semantic relations between headwords and dependents to perform semantic analysis on Chinese sentences. The classifier was able to achieve an accuracy of over 84%. We then analyze the errors in classification to determine the problems and possible solutions for this type of semantic analysis.