Autores
Gelbukh Alexander
Título Textual Entailment Using Lexical and Syntactic Similarity
Tipo Revista
Sub-tipo De difusión
Descripción International Journal of Artificial Intelligence & Applications (IJAIA)
Resumen A two-way Textual Entailment (TE) recognition system that uses lexical and syntactic features has been described in this paper. The TE system is rule based that uses lexical and syntactic similarities. The important lexical similarity features that are used in the present system are: WordNet based uni-gram match, bi-gram match, longest common sub-sequence, skip-gram, stemming. In the syntactic TE system, the important features used are: subject-subject comparison, subject-verb comparison, object-verb comparison and cross subject-verb comparison. The system has been separately trained on each development corpus released as part of the Recognising Textual Entailment (RTE) competitions RTE-1, RTE-2, RTE-3 and RTE-5 and tested on the respective RTE test sets. No separate development data was released in RTE-4. The evaluation results on each test set are compared with the RTE systems that participated in the respective RTE competitions with lexical and syntactic approaches.
Observaciones
Lugar
País
No. de páginas 43-58
Vol. / Cap. Vol. 2 No. 1
Inicio 2011-01-01
Fin
ISBN/ISSN