Recognizing textual entailment (TE) is a complex task involving knowledge from many different sources. One major source of information in this task is event factuality, since the ...
Texts are commonly interpreted based on the entire discourse in which they are situated. Discourse processing has been shown useful for inference-based application; yet, most syst...
Shachar Mirkin, Jonathan Berant, Ido Dagan, Eyal S...
This paper studies textual inference by investigating comma structures, which are highly frequent elements whose major role in the extraction of semantic relations has not been hi...
Vivek Srikumar, Roi Reichart, Mark Sammons, Ari Ra...
We address a core aspect of the multilingual content synchronization task: the identification of novel, more informative or semantically equivalent pieces of information in two d...
This paper focuses on the central role played by lexical information in the task of Recognizing Textual Entailment. In particular, the usefulness of lexical knowledge extracted fr...