Semantic Textual Entailment Recognition using UNL



Document title: Semantic Textual Entailment Recognition using UNL
Journal: Polibits
Database: PERIÓDICA
System number: 000358998
ISSN: 1870-9044
Authors: 1
1
1
2
Institutions: 1Jadavpur University, Computer Science and Engineering Department, Calcuta, Bengala Occidental. India
2Instituto Politécnico Nacional, Centro de Investigación en Computación, México, Distrito Federal. México
Year:
Season: Ene-Jun
Number: 43
Country: México
Language: Inglés
Document type: Artículo
Approach: Analítico, descriptivo
English abstract A two–way textual entailment (TE) recognition system that uses semantic features has been described in this paper. We have used the Universal Networking Language (UNL) to identify the semantic features. UNL has all the components of a natural language. The development of a UNL based textual entailment system that compares the UNL relations in both the text and the hypothesis has been reported. The semantic TE system has been developed using the RTE–3 test annotated set as a development set (includes 800 text–hypothesis pairs). Evaluation scores obtained on the RTE–4 test set (includes 1000 text–hypothesis pairs) show 55.89% precision and 65.40% recall for YES decisions and 66.50% precision and 55.20% recall for NO decisions and overall 60.3% precision and 60.3% recall
Disciplines: Ciencias de la computación,
Literatura y lingüística
Keyword: Procesamiento de datos,
Lingüística aplicada,
Lingüística computacional,
Vinculación textual,
Lenguaje universal de redes
Keyword: Computer science,
Literature and linguistics,
Data processing,
Applied linguistics,
Computing linguistics,
Textual entailment,
Universal networking language
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