JU_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 four way classification tasks (forward, backward, bidirectional and no-entailment). We set up different heuristics and measures for evaluating the entailment between two texts based on lexical relations. Experiments have been carried out with both the text and hypothesis converted to the same language using the Microsoft Bing translation system. The entailment system considers Named Entity, Noun Chunks, Part of speech, N-Gram and some text similarity measures of the text pair to decide the entailment judgments. Rules have been developed to encounter the multi way entailment issue. Our system decides on the entailment judgment after comparing the entailment scores for the text pairs. Four different rules have been developed for the four different classes of entailment. The best run is submitted for Italian -- English language with accuracy 0.326.