Work

Syntactic Testsuites and Textual Entailment Recognition

Year: 2010

Type: conference-paper

Abstract: We focus on textual entailments mediated by syntax and propose a new methodology to evaluate textual entailment recognition systems on such data.The main idea is to generate a syntactically annotated corpus of pairs of (non-)entailments and to use error mining to identify the most likely sources of errors.To illustrate the approach, we apply this methodology to the Afazio RTE system and show how it permits identifying the most likely sources of errors made by this system on a testsuite of 10 000 (non) entailment pairs.

Source: Language Resources and Evaluation Conference (LREC)

DOI: 10.63317/5gzp4dr7c9w3

Authors: Paul Bedaride, Claire Gardent

Institutions: Centre National de la Recherche Scientifique, Institut national de recherche en sciences et technologies du numérique, Laboratoire Lorrain de Recherche en Informatique et ses Applications, Université Henri Poincaré

Language: English

Topic: Natural Language Processing Techniques

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: hybrid

OpenAlex ID: W1553679662

FWCI:

Cites: 5

Cited by:

Related to: 20