This paper proposes a general probabilistic setting that formalizes the notion of textual entailment. In addition we describe a concrete model for lexical entailment based on web co-occurrence statistics in a bag of words representation.

this bipartite paper examines the function of tasrif in the quranic story of creation in the light of halliday's textual meta-function. first, the quranic concept of tasrif as a field in elm-al maani (semantics of syntax), and its relation to systemic linguistics is introduced and reviewed. then, through review of literature, it is referred to givenness hierarchy, empathy degree, point of ...

This paper presents a system that compositionally maps outputs of a wide-coverage Japanese CCG parser onto semantic representations and performs automated inference in higher-order logic. The system is evaluated on a textual entailment dataset. It is shown that the system solves inference problems that focus on a variety of complex linguistic phenomena, including those that are difficult to rep...

This paper presents a general-purpose open source package for recognizing Textual Entailment. The system implements a collection of algorithms, providing a configurable framework to quickly set up a working environment to experiment with the RTE task. Fast prototyping of new solutions is also allowed by the possibility to extend its modular architecture. We present the tool as a useful resource...

This paper presents the task on the evaluation of Compositional Distributional Semantics Models on full sentences organized for the first time within SemEval2014. Participation was open to systems based on any approach. Systems were presented with pairs of sentences and were evaluated on their ability to predict human judgments on (i) semantic relatedness and (ii) entailment. The task attracted...

Entailment pairs are sentence pairs of a premise and a hypothesis, where the premise textually entails the hypothesis. Such sentence pairs are important for the development of Textual Entailment systems. In this paper, we take a closer look at a prominent strategy for their automatic acquisition from newspaper corpora, pairing first sentences of articles with their titles. We propose a simple l...

In this paper, we describe the IMTKU (Information Management at TamKang University) textual entailment system for recognizing inference in text at NTCIR-10 RITE-2 (Recognizing Inference in Text). We proposed a textual entailment system using a hybrid approach that integrate semantic features and machine learning techniques for recognizing inference in text at NTCIR-10 RITE-2 task. We submitted ...

This paper presents a novel approach to Question Answering over structured data, which is based on Textual Entailment recognition. The main idea is that the QA problem can be recast as an entailment problem, where the text (T ) is the question and the hypothesis (H ) is a relational pattern, which is associated to “instructions” for retrieving the answer to the question. In this framework, give...

This paper describes the Bar-Ilan system participating in the Recognising Textual Entailment Challenge. The paper proposes first a general probabilistic setting that formalizes the notion of textual entailment. We then describe a concrete alignment-based model for lexical entailment, which utilizes web co-occurrence statistics in a bag of words representation. Finally, we report the results of ...

The Textual Entailment task has become influential in NLP and many researchers have become interested in applying it to other tasks. However, the two major issues emerging from this body of work are the fact that NLP applications need systems that (1) attain results which are not corpus dependent and (2) assume that the text for entailment cannot be incorrect or even contradictory. In this pape...