Error mining in parsing results

Authors:
Benoît Sagot;Éric de la Clergerie
Affiliations:
INRIA, Le Chesnay Cedex, France;INRIA, Le Chesnay Cedex, France
Venue:
ACL-44 Proceedings of the 21st International Conference on Computational Linguistics and the 44th annual meeting of the Association for Computational Linguistics
Year:
2006

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Abstract

We introduce an error mining technique for automatically detecting errors in resources that are used in parsing systems. We applied this technique on parsing results produced on several million words by two distinct parsing systems, which share the syntactic lexicon and the pre-parsing processing chain. We were thus able to identify missing and erroneous information in these resources.