Please use this identifier to cite or link to this item:
Title: Semantic Processing for Text Entailment with VENSES
Authors: Delmonte, Rodolfo
Tonelli, Sara
Tripodi, Rocco
Keywords: Text Entailment, Deep Text Processing, Semantics, Evaluation
Issue Date: Dec-2009
Publisher: NIST - National Institute of Standards in Technology
Abstract: In this paper we present two new mechanisms we created in VENSES, the system for semantic evaluation of the University of Venice. The first mechanism is used to match predicate-argument structures with different governors, a verb and a noun, respectively in the Hypothesis and the Text. It can be defined Augmented Finite State Automata (FSA) which are matching procedures based on tagged words in one case, and dependency relations in another. In both cases, a number of inferences – the augmentation - is fired to match different words. The second mechanism is based on the output of our module for anaphora resolution. Our system produces antecedents for pronominal expressions and equal nominal expressions. On the contrary, no decision is taken for “bridging” expressions. So the “bridging” mechanism is activated by the Semantic Evaluator and has access to the History List and the semantic features associated to each referring expression. If constraint conditions meet, the system looks for a similar association of property/entity in web ontologies like Umbel, Yago and DBPedia. The two mechanisms have been proven to contribute a 5% and 3% accuracy, respectively.
Appears in Collections:Articles, book chapters by CLS members

Files in This Item:
File Description SizeFormat 
VensesTeam.proceedings.pdf550.03 kBAdobe PDFView/Open

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.