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Implicature

19 paper cards from Mova's library

What it is

An implicature is what a speaker means without saying it. Asked «Did you like the play?», someone who answers «The costumes were nice» has said nothing about the play, yet everyone hears that they did not like it. «Some of the students passed» suggests that not all of them did, though it would be true if all had.

The philosopher Paul Grice explained this with the cooperative principle: listeners assume a speaker is being as informative, truthful, relevant and clear as the talk requires, and read extra meaning into an answer that seems to break one of these maxims. Implicatures can be cancelled («some, in fact all, passed»), which is what separates them from what a sentence strictly means.

How Mova does it

Mova's pragmatics infers implicatures by rule, each with its reason: a weaker word of a scale implicates that the stronger ones do not hold («some» → not all), except under negation, beside a stronger word, or when the speaker cancels it («in fact all»); a question implicates that the speaker does not know its answer; two event verbs joined by «and» are told in the order they happened. Presuppositions of triggers such as «again», «stop» and «regret» come beside them. The rules follow the maxim axioms of the rule-based literature.

The papers (19)

Cards with a measured or kept idea first, then by citations.

  1. Investigating the distribution of some (but not all) implicatures using corpora and web-based methods — Judith Degen, 2015 · 128 citations
  2. Raising and resolving issues with scalar modifiers — Elizabeth Coppock, Thomas Brochhagen, 2013 · 128 citations
  3. Are Natural Language Inference Models IMPPRESsive? Learning IMPlicature and PRESupposition — Paloma Jeretic, Alex Warstadt, Suvrat Bhooshan, Adina Williams, 2020 · 77 citations
  4. Probability and implicatures: A unified account of the scalar effects of disjunction under modals — Paolo Santorio, Jacopo Romoli, 2017 · 34 citations
  5. A practical introduction to the Rational Speech Act modeling framework — Gregory Scontras, Michael Henry Tessler, Michael Franke, 2021 · 27 citations
  6. Computational Interpretations of the Gricean Maxims in the Generation of Referring Expressions — Robert Dale, Ehud Reiter, 1995 · 25 citations
  7. GRICE: A Grammar-based Dataset for Recovering Implicature and Conversational rEasoning — Zilong Zheng, Shuwen Qiu, Lifeng Fan, Yixin Zhu et al., 2021 · 12 citations
  8. The Role of the Gricean Maxims in the Generation of Referring Expressions — Robert Dale, Ehud Reiter, 1996 · 10 citations
  9. The role of Alternatives in the interpretation of scalars and numbers: Insights from the inference task — Chao Sun, Richard Breheny, 2022 · 6 citations
  10. The Gricean Maxims in NLP — A Survey — Lea Krause, Piek T.J.M. Vossen, 2024 · 4 citations
  11. "Is the Pope Catholic?" Applying Chain-of-Thought Reasoning to Understanding Conversational Implicatures — Zae Myung Kim, David E. Taylor, Dongyeop Kang, 2023 · 1 citations
  12. Can Your Model Tell a Negation from an Implicature? Unravelling Challenges With Intent Encoders — Yuwei Zhang, Siffi Singh, Sailik Sengupta, Igor Shalyminov et al., 2024
  13. SIGA: A Naturalistic NLI Dataset of English Scalar Implicatures with Gradable Adjectives — Rashid Nizamani, Sebastian Schuster, Vera Demberg, 2024
  14. Survey on Computational Approaches to Implicature — Kaveri Anuranjana, Srihitha Mallepally, Sriharshitha Mareddy, Amit Shukla et al., 2024
  15. Conversational implicatures in English dialogue: Annotated dataset — Elizabeth Jasmi George, Radhika Mamidi, 2019
  16. Scalar Implicatures: Pragmatic Inferences or Grammar? — Chungmin Lee, 2008
  17. Computing relative polarity for textual inference — Rowan Nairn, Cleo Condoravdi, Lauri Karttunen, 2006
  18. Pragmatic information extraction from subject ellipsis in informal English — Shigeko Nariyama, 2006
  19. Preventing False Temporal Implicatures: Interactive Defaults for Text Generation — Jon Oberlander, Alex Lascarides, 1992

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