| Journal: | Computación y sistemas |
| Database: | PERIÓDICA |
| System number: | 000395006 |
| ISSN: | 1405-5546 |
| Authors: | Basak, Rohini1 Naskar, Sudip Kumar1 Pakray, Partha2 Gelbukh, Alexander3 |
| Institutions: | 1Jadavpur University, Calcuta, Bengala Occidental. India 2National Institute of Technology Mizoram, Aizawl. India 3Instituto Politécnico Nacional, Centro de Investigación en Computación, México, Distrito Federal. México |
| Year: | 2015 |
| Season: | Oct-Dic |
| Volumen: | 19 |
| Number: | 4 |
| Pages: | 685-700 |
| Country: | México |
| Language: | Inglés |
| Document type: | Artículo |
| Approach: | Analítico |
| English abstract | We present a rule-based method for recognizing entailment relation between a pair of text fragments by comparing their dependency tree structures. We used a dependency parser to generate the dependency triples of the text-hypothesis pairs. A dependency triple is an arc in the dependency parse tree. Each triple in the hypothesis is checked against all the triples in the text to find a matching pair. We have developed a number of matching rules after a detailed analysis of the PETE dataset, which we used for the experiments. A successful match satisfying any of these rules assigns a matching score of 1 to the child node of that particular arc in the hypothesis dependency tree. Then the dependency parse tree is traversed in post-order way to obtain the final entailment score at the root node. The scores of the leaf nodes are propagated from the bottom of the tree to the non-leaf nodes, up to the root node. The entailment score of the root node is compared against a predefined threshold value to make the entailment decision. Experimental results on the PETE dataset show an accuracy of 87.69% on the development set and 73.75% on the test set, which outperforms the state-of-the-art results reported on this dataset so far. We did not use any other NLP tools or knowledge sources, to emphasize the role of dependency parsing in recognizing textual entailment |
| Disciplines: | Ciencias de la computación, Literatura y lingüística |
| Keyword: | Procesamiento de datos, Lingüística aplicada, Vinculación textual, Análisis de dependencias, Lingüística computacional, Textos, Paráfrasis |
| Keyword: | Computer science, Literature and linguistics, Data processing, Applied linguistics, Textual entailment, Dependency parsing, Computing linguistics, Texts, Paraphrase |
| Full text: | Texto completo (Ver PDF) |
