This study aimed to investigate the impact of textual enhancement and metalinguistic explanation as focus-on-form tasks tending to encourage the acquisition of nominal clauses (NCs) in English. It explored (a) whether textual enhancement and metalinguistic explanation would promote and enhance the knowledge of NCs, (b) whether these two tasks would differ in terms of enhancing learners' knowled...

Large-scale mathematical models are built, managed and applied by people with different cognitive skills. This poses a challenge for the design of a multi-view architecture of a system that accommodates these differences. A primary objective of mathematical modeling is providing insights into problem behavior, and there are many constituencies who require different views for different questions...

The increasing size of structured data that are digitally available emphasizes the crucial need for more suitable representation tools than the traditional textual list of results. A suitable visual representation should both reflect the database’s structure for navigation purpose and allow performing visual analytical tasks for knowledge extraction purpose. In this paper we present a visual na...

The increasing size of indexed document sets that are digitally available emphasizes the crucial need for more suitable representation tools than traditional textual lists of results. Many efforts have been made to develop graphical tools capable of providing both overall and local views of a collection when focusing on a particular subset of documents. However an overcrowded visual representat...

This paper presents the second round of the task on Cross-lingual Textual Entailment for Content Synchronization, organized within SemEval-2013. The task was designed to promote research on semantic inference over texts written in different languages, targeting at the same time a real application scenario. Participants were presented with datasets for different language pairs, where multi-direc...

This paper proposes a methodology for generating specialized Japanese data sets for textual entailment, which consists of pairs decomposed into basic sentence relations. We experimented with our methodology over a number of pairs taken from the RITE-2 data set. We compared our methodology with existing studies in terms of agreement, frequencies and times, and we evaluated its validity by invest...

In this paper, we first compare several strategies to handle the newly proposed three-way Recognizing Textual Entailment (RTE) task. Then we define a new measurement for a pair of texts, called Textual Relatedness, which is a weaker concept than semantic similarity or paraphrase. We show that an alignment model based on the predicate-argument structures using this measurement can help an RTE sy...

In this paper we present a classifier for Recognising Textual Entailment (RTE) and Semantic Equivalence. We evaluate the performance of this classifier using an evaluation framework provided by the PASCAL RTE Challenge Workshop. Sentence–pairs are represented as a set of features, which are used by our decision tree classifier to determine if an entailment relationship exisits between each sent...

We present two regression models for the prediction of pairwise preference judgments among MT hypotheses. Both models are based on feature sets that are motivated by textual entailment and incorporate lexical similarity as well as local syntactic features and specific semantic phenomena. One model predicts absolute scores; the other one direct pairwise judgments. We find that both models are co...