Benchmarking for syntax-based sentential inference

Paul Bedaride 1 Claire Gardent 1
1 TALARIS - Natural Language Processing: representation, inference and semantics
Inria Nancy - Grand Est, LORIA - Laboratoire Lorrain de Recherche en Informatique et ses Applications
Abstract : We propose a methodology for investigat- ing how well NLP systems handle mean- ing 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 seman- tic role labeller and two grammar based RTE systems. We argue that the proposed methodology (i) supports a modular eval- uation of the ability of NLP systems to handle the syntax/semantic interface and (ii) permits focused error mining and er- ror analysis.
Document type :
Conference papers
Complete list of metadatas

Cited literature [20 references]  Display  Hide  Download

https://hal.inria.fr/inria-00536022
Contributor : Paul Bedaride <>
Submitted on : Monday, November 15, 2010 - 9:44:09 AM
Last modification on : Thursday, January 11, 2018 - 6:21:35 AM
Long-term archiving on : Friday, October 26, 2012 - 3:40:19 PM

File

bedgar-acl10-coling10.pdf
Files produced by the author(s)

Identifiers

  • HAL Id : inria-00536022, version 1

Collections

Citation

Paul Bedaride, Claire Gardent. Benchmarking for syntax-based sentential inference. The 23rd International Conference on Computational Linguistics - COLING 2010, Aug 2010, Beijing, China. ⟨inria-00536022⟩

Share

Metrics

Record views

232

Files downloads

115