TY  - JOUR
AU  - de Barcelos Silva, Allan 
AU  - Rigo, Sandro José 
PY  - 2018
TI  - Enhancing Brazilian Portuguese Textual Entailment Recognition with a Hybrid Approach
JF  - Journal of Computer Science
VL  - 14
IS  - 7
DO  - 10.3844/jcssp.2018.945.956
UR  - https://thescipub.com/abstract/jcssp.2018.945.956
AB  - Previous work on textual entailment has not fully exploited aspects of deep linguistic relations, which have been shown as containing important information for entailment identification. In this study, we present a new method to compute semantic textual similarity between two sentences. Our proposal relies on the integration of a set of deep linguistic relations, lexical aspects and distributed representational resources. We used our method with a large set of annotated data available from the ASSIN Workshop in the PROPOR 2016 event. The achieved results score among the best-known results in the literature. A perceived advantage of our approach is the ability to generate good results even with a small corpus on training tasks.