The benefits of textual input enhancement in the acquisition of linguistic forms have produced mixed results in SLA literature. The present study investigates the effects of textual enhancement on adult foreign language intake of two English linguistic forms-subjunctive mood and inversion structures-to explore the role of the type of linguistic items in input enhancement studies. It also invest...

the benefits of textual input enhancement in the acquisition of linguistic forms have produced mixed results in sla literature. the present study investigates the effects of textual enhancement on adult foreign language intake of two english linguistic forms-subjunctive mood and inversion structures-to explore the role of the type of linguistic items in input enhancement studies. it also invest...

In this paper, we propose a pseudo-relevance feedbackmethod to deal with the photographic retrieval and medical retrieval tasks of ImageCLEF 2007. The aim of our participation to ImageCLEF is to evaluate a combination method using both english textual queries and image queries to answer to topics. The approach processes image queries and merges them with textual queries in order to improve resu...

We present an approach to perform external plagiarism analysis by applying several similarity detection techniques, such as lexical measures and a textual entailment recognition system developed by our research group. Some of the least expensive features of this system are applied to all corpus documents to detect those that are likely to be plagiarized. After this is done, the whole system is ...

We introduce a new approach to training a semantic parser that uses textual entailment judgements as supervision. These judgements are based on high-level inferences about whether the meaning of one sentence follows from another. When applied to an existing semantic parsing task, they prove to be a useful tool for revealing semantic distinctions and background knowledge not captured in the targ...

This paper presents a system that uses machine learning algorithms and a combination of data sets for the task of recognizing textual entailment. The chosen features quantify lexical, syntactic and semantic level by matching between texts and hypothesis sentences. Additionally, we created a filter which uses a set of heuristics based on Named Entities to detect cases where no entailment was fou...

This paper advocates a new architecture for textual inference in which finding a good alignment is separated from evaluating entailment. Current approaches to semantic inference in question answering and textual entailment have approximated the entailment problem as that of computing the best alignment of the hypothesis to the text, using a locally decomposable matching score. We argue that the...

This paper proposes a new architecture for textual inference in which finding a good alignment is separated from evaluating entailment. Current approaches to semantic inference in question answering and textual entailment have approximated the entailment problem as that of computing the best alignment of the hypothesis to the text, using a locally decomposable matching score. While this formula...

the benefits of textual input enhancement in the acquisition of linguistic forms have produced mixed results in sla literature. the present study investigates the effects of textual enhancement on adult foreign language intake of two english linguistic forms-subjunctive mood and inversion structures-to explore the role of the type of linguistic items in input enhancement studies. it also invest...