In this paper, we explore the application of inference rules for recognizing textual entailment (RTE). We start with an automatically acquired collection and then propose methods to refine it and obtain more rules using a hand-crafted lexical resource. Following this, we derive a dependency-based representation from texts, which aims to provide a proper base for the inference rule application. ...

We present the results of the Joint Student Response Analysis and 8th Recognizing Textual Entailment Challenge, aiming to bring together researchers in educational NLP technology and textual entailment. The task of giving feedback on student answers requires semantic inference and therefore is related to recognizing textual entailment. Thus, we offered to the community a 5-way student response ...

In this paper we define two intermediate models of textual entailment, which correspond to lexical and lexical-syntactic levels of representation. We manually annotated a sample from the RTE dataset according to each model, compared the outcome for the two models, and explored how well they approximate the notion of entailment. We show that the lexicalsyntactic model outperforms the lexical mod...

We present a Textual Entailment (TE) recognition system that uses semantic features based on the Universal Networking Language (UNL). The proposed TE system compares the UNL relations in both the text and the hypothesis to arrive at the two-way entailment decision. The system has been separately trained on each development corpus released as part of the Recognizing Textual Entailment (RTE) comp...

Our system combines text similarity measures with a textual entailment system. In the main task, we focused on the influence of lexicalized versus unlexicalized features, and how they affect performance on unseen questions and domains. We also participated in the pilot partial entailment task, where our system significantly outperforms a strong baseline.

the present study investigated comparatively the impact of two types of input enhancement (i.e. textual vs. compound enhancement) on developing grammar ability in iranian efl setting. sixty-five female secondary high school students were selected as a homogenous sample out of about a 100-member population based on nelson language proficiency test. then, their grammar ability was measured based ...

The present study examined the effect of multimedia glosses on foreign language listening comprehension. To this end, 94 male students studying at Rasa English Institute in Tehran were selected for the treatment. The participants consisted of three groups, and each group was randomly assigned to one of the following treatment conditions: textual, pictorial, and textual-pictorial glossing....

An artificial believer has to recognize textual entailment to categorize beliefs. We describe our system – the Fuzzy Believer system – and its application to the TAC/RTE three-way task.

This paper describes the IBM team's approach for the textual entailment recognition task (RITE) in NTCIR-9 [10] with experimental results for four Japanese subtasks: BC, MC, EXAM, and RITE4QA. To tackle the data set with complicated syntactic and semantic phenomena, the authors used a classi cation method to predict entailment relations between two di erent texts. These features were used for c...