Process / pipeline

Textual Entailment — Natural Language Inference (NLI)

Textual entailment, also known as natural language inference (NLI), is the natural-language-processing task of deciding whether one piece of text (the premise) entails a second piece of text (the hypothesis), contradicts it, or is neutral with respect to it. Formalised by the PASCAL Recognising Textual Entailment Challenge (Dagan, Glickman & Magnini, 2006) and broadened by the MultiNLI corpus (Williams, Nangia & Bowman, 2018), it underpins question answering and fact-verification pipelines.

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Sources

  1. Dagan, I., Glickman, O. & Magnini, B. (2006). The PASCAL Recognising Textual Entailment Challenge. link
  2. Williams, A., Nangia, N. & Bowman, S. (2018). A Broad-Coverage Challenge Corpus for Sentence Understanding through Inference. NAACL. link

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Referenced by

ScholarGateTextual Entailment (Textual Entailment (Natural Language Inference, NLI)). Retrieved 2026-06-04 from https://scholargate.app/en/text-mining/textual-entailment