Detecting errors in English article usage by non-native speakers
Natural Language Engineering
Formal systems for persuasion dialogue
The Knowledge Engineering Review
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
Native judgments of non-native usage: experiments in preposition error detection
HumanJudge '08 Proceedings of the Workshop on Human Judgements in Computational Linguistics
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In this short paper, we present annotations for tagging grammatical and stylistic errors, together with attributes about the nature of the correction which are then interpreted as arguments. A decision model is introduced in order for the author to be able to decide on the best correction to make. This introduces an operational semantics for tags and related attributes.