Work

Combining lexical-syntactic information with machine learning for recognizing textual entailment

Year: 2007

Type: conference-paper

Abstract: This document contains the description of the experiments carried out by SINAI group.We have developed an approach based on several lexical and syntactic measures integrated by means of different machine learning models.More precisely, we have evaluated three features based on lexical similarity and 11 features based on syntactic tree comparison.In spite of the relatively straightforward approach we have obtained more than 60% for accuracy.Since this is our first participation we think we have reached a good result.

Source: ACL-PASCAL Workshop on Textual Entailment and Paraphrasing (RTE)

DOI: 10.3115/1654536.1654553

Authors: Arturo Montejo-Ráez, Jose Manuel Perea, Fernando Martínez-Santiago, Miguel Ángel García-Cumbreras, Maite Martín-Valdivia, Alfonso Ureña-López

Institution: Universidad de Jaén

Language: English

Topic: Natural Language Processing Techniques

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: bronze

Funder: Universidad de Jaén

OpenAlex ID: W2024761006

FWCI: 0.866

Cites: 6

Cited by: 5

Related to: 10