Textual entailment recognition is the task of deciding, given two text fragments, whether the meaning of one text can be deduced from the other. This year, at our fourth participation in the RTE competition, we improved the system built for the RTE-5 competition. Our system solves entailment by attempting to map every word in the hypothesis to one or more words in the text. For that, we transfo...

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.

A global field experiment with Seeking Alpha shows that textual complexity affects investor attention to news and market outcomes. Investors were randomly assigned different titles for the same article. Holding article fixed, a one-standard-deviation increase in leads 6.1% fewer views. Complexity is more off-putting less-sophisticated investors, when limited, likely less important. Exploiting a...

Russian ecological literature writers and British "Lake Poets School" in the 19th century were determined to build their literary values by appreciating natural world. Due diverse circumstances as well personal experiences, two countries' have respective views on nature, ecology, attitudes towards life, writing styles. Based issues above, this paper conducts a detailed textual reading of works ...

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 ...