CELI: An Experiment with Cross Language Textual Entailment
نویسندگان
چکیده
This paper presents CELI’s participation in the SemEval Cross-lingual Textual Entailment for Content Synchronization task.
منابع مشابه
Celi: EDITS and Generic Text Pair Classification
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).
متن کاملTowards Cross-Lingual Textual Entailment
This paper investigates cross-lingual textual entailment as a semantic relation between two text portions in different languages, and proposes a prospective research direction. We argue that cross-lingual textual entailment (CLTE) can be a core technology for several cross-lingual NLP applications and tasks. Through preliminary experiments, we aim at proving the feasibility of the task, and pro...
متن کاملJU_CSE_NLP: Language Independent Cross-lingual Textual Entailment System
This article presents the experiments carried out at Jadavpur University as part of the participation in Cross-lingual Textual Entailment for Content Synchronization (CLTE) of task 8 @ Semantic Evaluation Exercises (SemEval-2012). The work explores cross-lingual textual entailment as a relation between two texts in different languages and proposes different measures for entailment decision in a...
متن کاملText Grouping using Textual Entailment
Textual Entailment is an important field in Natural Language Processing domain. Given two texts called T (Text) and H (Hypothesis), the textual entailment recognition is the task of deciding whether the meaning of H can be logically inferred from that of T. A Textual Entailment (TE) system has developed and this system has tested on various entailment standard datasets. This TE will apply to di...
متن کاملFBK: Cross-Lingual Textual Entailment Without Translation
This paper overviews FBK’s participation in 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 phrase tables and dependency relations. The features are used for multi-class and binary classification using SVMs. Using a combination of l...
متن کامل