Recognizing textual entailment in non-English text via automatic translation into English

Partha Pakray, Snehasis Neogi, Sivaji Bandyopadhyay, Alexander Gelbukh

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Resumen

We show that a task that typically involves rather deep semantic processing of text-being recognizing textual entailment our case study-can be successfully solved without any tools at all specific for the language of the texts on which the task is performed. Instead, we automatically translate the text into English using a standard machine translation system, and then perform all linguistic processing, including syntactic and semantic levels, using only English language linguistic tools. In this case study we use Italian annotated data. Textual entailment is a relation between two texts. To detect it, we use various measures, which allow us to make entailment decision in the two-way classification task (yes / no). We set up various heuristics and measures for evaluating the entailment between two texts based on lexical relations. To make entailment judgments, the system applies named entity recognition module, chunking, part-of-speech tagging, n-grams, and text similarity modules to both texts, all those modules being for English and not for Italian. Rules have been developed to perform the two-way entailment classification. Our system makes entailment judgments basing on the entailment scores for the text pairs. The system was evaluated on Italian textual entailment data sets: we trained our system on Italian development datasets using the WEKA machine learning toolset and tested it on Italian test data sets. The accuracy of our system on the development corpus is 0.525 and on the test corpus is 0.66, which is a good result given that no Italian-specific linguistic information was used.

Idioma originalInglés
Título de la publicación alojadaAdvances in Artificial Intelligence - 11th Mexican International Conference on Artificial Intelligence, MICAI 2012, Revised Selected Papers
Páginas26-35
Número de páginas10
EdiciónPART 2
DOI
EstadoPublicada - 2013
Evento11th Mexican International Conference on Artificial Intelligence, MICAI 2012 - San Luis Potosi, México
Duración: 27 oct. 20124 nov. 2012

Serie de la publicación

NombreLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NúmeroPART 2
Volumen7630 LNAI
ISSN (versión impresa)0302-9743
ISSN (versión digital)1611-3349

Conferencia

Conferencia11th Mexican International Conference on Artificial Intelligence, MICAI 2012
País/TerritorioMéxico
CiudadSan Luis Potosi
Período27/10/124/11/12

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