Semantic construction in feature-based TAG
EACL '03 Proceedings of the tenth conference on European chapter of the Association for Computational Linguistics - Volume 1
Error mining in parsing results
ACL-44 Proceedings of the 21st International Conference on Computational Linguistics and the 44th annual meeting of the Association for Computational Linguistics
Dependency-based syntactic-semantic analysis with PropBank and NomBank
CoNLL '08 Proceedings of the Twelfth Conference on Computational Natural Language Learning
Software testing and the naturally occurring data assumption in natural language processing
SETQA-NLP '08 Software Engineering, Testing, and Quality Assurance for Natural Language Processing
Intrinsic versus extrinsic evaluations of parsing systems
Evalinitiatives '03 Proceedings of the EACL 2003 Workshop on Evaluation Initiatives in Natural Language Processing: are evaluation methods, metrics and resources reusable?
The third PASCAL recognizing textual entailment challenge
RTE '07 Proceedings of the ACL-PASCAL Workshop on Textual Entailment and Paraphrasing
A semantic approach to textual entailment: system evaluation and task analysis
RTE '07 Proceedings of the ACL-PASCAL Workshop on Textual Entailment and Paraphrasing
A generalized method for iterative error mining in parsing results
GEAF '09 Proceedings of the 2009 Workshop on Grammar Engineering Across Frameworks
Deep semantics for dependency structures
CICLing'11 Proceedings of the 12th international conference on Computational linguistics and intelligent text processing - Volume Part I
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We propose a methodology for investigating how well NLP systems handle meaning preserving syntactic variations. We start by presenting a method for the semi automated creation of a benchmark where entailment is mediated solely by meaning preserving syntactic variations. We then use this benchmark to compare a semantic role labeller and two grammar based RTE systems. We argue that the proposed methodology (i) supports a modular evaluation of the ability of NLP systems to handle the syntax/semantic interface and (ii) permits focused error mining and error analysis.