Межъязыковое Текстовое Следование

This paper explores the use of bilingual par- allel corpora as a source of lexical knowl- edge for cross-lingual textual entailment. We claim that, in spite of the inherent difficul- …...

In this paper we present a report of the two di- fferent runs submitted to the task 8 of Semeval 2012 for the evaluation of Cross-lingual Tex- tual Entailment in …...

inThis paper overviews FBK’s participation the Cross-Lingual Textual Entailment for Content Synchronization task organized within SemEval-2012. Our participation is characterized by using cross-lingual matching features extracted from lexical and semantic …...

We describe the Heidelberg University system for the Cross-lingual Textual Entailment task at SemEval-2012. The system relies on fea- tures extracted with statistical machine trans- lation methods and tools, combining …...

In this paper, we present our system descrip- tion in task of Cross-lingual Textual Entail- ment. The goal of this task is to detect entailment relations between two sentences written …...

This article presents the experiments car- ried out at Jadavpur University as part of the participation in Cross-lingual Textual Entailment for Content Synchronization (CLTE) of task 8 @ Semantic Evaluation …...

We address two challenges for automatic ma- chine translation evaluation: a) avoiding the use of reference translations, and b) focusing on adequacy estimation. From an economic perspective, getting rid of …...

This paper describes our participation in the task denominated Cross-Lingual Textual En- tailment (CLTE) for content synchronization. We represent an approach to CLTE using machine translation to tackle the problem …...

This paper presents the first round of the task on Cross-lingual Textual Entailment for Content Synchronization, organized within SemEval-2012. The task was designed to pro- mote research on semantic inference …...

This paper presents a novel approach for building adaptive similarity functions based on cardinality us- ing machine learning. Unlike current approaches that build feature sets using similarity scores, we have …...

This paper describes a new method for cross- lingual textual entailment (CLTE) detection based on machine translation (MT). We use sub-segment translations from different MT systems available online as a …...

We present a supervised learning approach to cross-lingual textual entailment that explores statistical word alignment models to predict entailment relations between sentences writ- ten in different languages. Our approach is …...

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

This paper presents our approach used for cross-lingual textual entailment task (task 8) organized within SemEval 2013. Cross- lingual textual entailment (CLTE) tries to de- tect the entailment relationship between …...

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 pro- mote research on semantic inference …...

This paper describes The University of Mel- bourne NLP group submission to the Cross- lingual Textual Entailment shared task, our first tentative attempt at the task. The ap- proach involves …...