The nature of statistical learning theory
The nature of statistical learning theory
Definiteness predictions for Japanese noun phrases
COLING '98 Proceedings of the 17th international conference on Computational linguistics - Volume 1
Countability and number in Japanese to English machine translation
COLING '94 Proceedings of the 15th conference on Computational linguistics - Volume 1
Using predicate-argument structures for information extraction
ACL '03 Proceedings of the 41st Annual Meeting on Association for Computational Linguistics - Volume 1
PENS: a machine-aided english writing system for Chinese users
ACL '00 Proceedings of the 38th Annual Meeting on Association for Computational Linguistics
The Alignment Template Approach to Statistical Machine Translation
Computational Linguistics
EMNLP '02 Proceedings of the ACL-02 conference on Empirical methods in natural language processing - Volume 10
Correcting ESL errors using phrasal SMT techniques
ACL-44 Proceedings of the 21st International Conference on Computational Linguistics and the 44th annual meeting of the Association for Computational Linguistics
Question answering based on semantic structures
COLING '04 Proceedings of the 20th international conference on Computational Linguistics
Collective semantic role labelling with Markov logic
CoNLL '08 Proceedings of the Twelfth Conference on Computational Natural Language Learning
Models for the semantic classification of noun phrases
CLS '04 Proceedings of the HLT-NAACL Workshop on Computational Lexical Semantics
The ups and downs of preposition error detection in ESL writing
COLING '08 Proceedings of the 22nd International Conference on Computational Linguistics - Volume 1
Combination strategies for semantic role labeling
Journal of Artificial Intelligence Research
Semantic role labeling: past, present and future
ACLTutorials '09 Tutorial Abstracts of ACL-IJCNLP 2009
Correcting verb selection errors for ESL with the perceptron
CICLing'11 Proceedings of the 12th international conference on Computational linguistics and intelligent text processing - Volume Part II
Engkoo: mining the web for language learning
HLT '11 Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies: Systems Demonstrations
Verb selection using semantic role labeling for citation classification
Proceedings of the 2013 workshop on Computational scientometrics: theory & applications
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In this paper we develop an approach to tackle the problem of verb selection for learners of English as a second language (ESL) by using features from the output of Semantic Role Labeling (SRL). Unlike existing approaches to verb selection that use local features such as n-grams, our approach exploits semantic features which explicitly model the usage context of the verb. The verb choice highly depends on its usage context which is not consistently captured by local features. We then combine these semantic features with other local features under the generalized perceptron learning framework. Experiments on both indomain and out-of-domain corpora show that our approach outperforms the baseline and achieves state-of-the-art performance.