Parsing schemata and correctness of parsing algorithms
AMiLP '95 Proceedings of the first international AMAST workshop on Algebraic methods in language processing
Syntax-directed least-errors analysis for context-free languages: a practical approach
Communications of the ACM
An efficient context-free parsing algorithm
Communications of the ACM
Error repair with validation in LR-based parsing
ACM Transactions on Programming Languages and Systems (TOPLAS)
Parsing Schemata: A Framework for Specification and Analysis of Parsing Algorithms
Parsing Schemata: A Framework for Specification and Analysis of Parsing Algorithms
Repairing syntax errors in LR-based parsers
ACSC '02 Proceedings of the twenty-fifth Australasian conference on Computer science - Volume 4
Repairing syntax errors in LR parsers
ACM Transactions on Programming Languages and Systems (TOPLAS)
Regional Least-Cost Error Repair
CIAA '00 Revised Papers from the 5th International Conference on Implementation and Application of Automata
Stochastic Error-Correcting Parsing for OCR Post-Processing
ICPR '00 Proceedings of the International Conference on Pattern Recognition - Volume 4
Charting the depths of robust speech parsing
ACL '99 Proceedings of the 37th annual meeting of the Association for Computational Linguistics on Computational Linguistics
A formal frame for robust parsing
Theoretical Computer Science - Implementation and application of automata
Syntax error repair for a Java-based parser generator
ACM SIGPLAN Notices
A compiler for parsing schemata
Software—Practice & Experience
Parsing Techniques: A Practical Guide
Parsing Techniques: A Practical Guide
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A desirable property for any system dealing with unrestricted natural language text is robustness, the ability to analyze any input regardless of its grammaticality. In this paper we present a novel, general transformation technique to automatically obtain robust, error-repair parsers from standard non-robust parsers. The resulting error-repair parsing schema is guaranteed to be correct when our method is applied to a correct parsing schema verifying certain conditions that are weak enough to be fulfilled by a wide variety of parsers used in natural language processing.