An unsupervised method for detecting grammatical errors
NAACL 2000 Proceedings of the 1st North American chapter of the Association for Computational Linguistics conference
StringNet as a computational resource for discovering and investigating linguistic constructions
EUCCL '10 Proceedings of the NAACL HLT Workshop on Extracting and Using Constructions in Computational Linguistics
EdIt: a broad-coverage grammar checker using pattern grammar
HLT '11 Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies: Systems Demonstrations
The StringNet lexico-grammatical knowledgebase and its applications
MWE '11 Proceedings of the Workshop on Multiword Expressions: from Parsing and Generation to the Real World
GRASP: grammar- and syntax-based pattern-finder in CALL
IUNLPBEA '11 Proceedings of the 6th Workshop on Innovative Use of NLP for Building Educational Applications
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We describe and motivate an unsupervised lexical error detection and correction algorithm and its application in a tool called Lexbar appearing as a query box on the Web browser toolbar or as a search engine interface. Lexbar accepts as user input candidate strings of English to be checked for acceptability and, where errors are detected, offers corrections. We introduce the notion of hybrid n-gram and extract these from BNC as the knowledgebase against which to compare user input. An extended notion of edit distance is used to identify most likely candidates for correcting detected errors. Results are illustrated with four types of errors.