In order for a text to entail a hypothesis, the text usually must mention all of the information in the hypothesis. We use this observation as a basis for a simple system for detecting non-entailment. Unlike many previous lexically-based systems, we do not measure the degree of overlap or similarity, and we do no machine learning. This simple system performs well on the Recognizing Textual Enta...

In this paper, we describe a method for assessing student answers, modeled as a paraphrase identification problem, based on substitution by Basic English variants. Basic English paraphrases are acquired from the Simple English Wiktionary. Substitutions are applied both on reference answers and student answers in order to reduce the diversity of their vocabulary and map them to a common vocabula...

This paper presents CELI’s participation in the SemEval The Joint Student Response Analysis and 8th Recognizing Textual Entailment Challenge (Task7) and Cross-lingual Textual Entailment for Content Synchronization task (Task 8).

This paper describes the Cambridge submission to the SemEval-2010 Parser Evaluation using Textual Entailment (PETE) task. We used a simple definition of entailment, parsing both T and H with the C&C parser and checking whether the core grammatical relations (subject and object) produced for H were a subset of those for T. This simple system achieved the top score for the task out of those syste...

This paper explores how a battery of unsupervised techniques can be used in order to create large, high-quality corpora for textual inference applications, such as systems for recognizing textual entailment (TE) and textual contradiction (TC). We show that it is possible to automatically generate sets of positive and negative instances of textual entailment and contradiction from textual corpor...

In this work we investigate methods to enable the detection of a specific type of textual entailment (strict entailment), starting from the preliminary assumption that these relations are often clearly expressed in texts. Our method is a statistical approach based on what we call textual entailment patterns, prototypical sentences hiding entailment relations among two activities. We experimente...

the purpose of the present study was to investigate the use of personal and impersonal metadiscourse (md) by persian- and english-speaking writers in academic writing. for this purpose, 80 abstracts were selected (40 written by persian-speaking writers and 40 by english-speaking ones) and analyzed. these abstracts were selected from endocrinology and metabolism journals published during 2010 to...