Abstract

RUDRAPAL, Dwijen; DAS, Amitava  and  BHATTACHARYA, Baby. Recognition of Partial Textual Entailment for Indian Social Media Text. Comp. y Sist. [online]. 2019, vol.23, n.1, pp.143-152.  Epub Feb 26, 2021. ISSN 2007-9737.  https://doi.org/10.13053/cys-23-1-2816.

Textual entailment (TE) is a unidirectional relationship between two expressions where the meaning of one expression called Hypothesis (H), infers from the other expression called Text (T). The definition of TE is rigid in a sense that if the H entails from T but lacks minor information or have some additional information, then the pair is treated as non-entailed. In such cases, we could not measure the relatedness of a T-H pair. Partial textual entailment (PTE) is a possible solution of this problem which defines partial entailment relation between a T-H pair. PTE relationship can plays an important role in different Natural Language Processing (NLP) applications like text summarization and question-answering system by reducing redundant information. In this paper we investigate the idea of PTE for Indian social media text (SMT). We developed a PTE annotated corpus for Bengali tweets and proposed a Sequential Minimal Optimization (SMO) based PTE recognition approach. We also evaluated our proposed approach through experiment results.

Keywords : Textual entailment; social media text; text summarization; partial textual entailment; question-answering system; machine learning.

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