# Conversational Negation using Worldly Context in Compositional Distributional Semantics

arXiv: https://arxiv.org/abs/2105.05748 · HTML: https://mlsanity.com/paper/2105.05748/

## Key facts

- Cited by 9 papers in the map (data through 14 Oct 2026).
- Builds on 10 of its 28 references that are in the map.
- First posted on arXiv 12 May 2021.

## Builds on (most cited first, 10 of 10)

- [Foundations for Near-Term Quantum Natural Language Processing](https://mlsanity.com/paper/2012.03755/) (2020)
- [Hearst Patterns Revisited: Automatic Hypernym Detection from Large Text Corpora](https://mlsanity.com/paper/1806.03191/) (2018)
- [The Mathematics of Text Structure](https://mlsanity.com/paper/1904.03478/) (2019)
- [Open System Categorical Quantum Semantics in Natural Language Processing](https://mlsanity.com/paper/1502.00831/) (2015)
- [Interacting Conceptual Spaces I : Grammatical Composition of Concepts](https://mlsanity.com/paper/1703.08314/) (2017)
- [Meaning updating of density matrices](https://mlsanity.com/paper/2001.00862/) (2020)
- [Towards logical negation for compositional distributional semantics](https://mlsanity.com/paper/2005.04929/) (2020)
- [Cats climb entails mammals move: preserving hyponymy in compositional distributional semantics](https://mlsanity.com/paper/2005.14134/) (2020)
- ["Not not bad" is not "bad": A distributional account of negation](https://mlsanity.com/paper/1306.2158/) (2013)
- [Distributional Sentence Entailment Using Density Matrices](https://mlsanity.com/paper/1506.06534/) (2015)

## Built on by (most cited first, 9 of 9)

- [Composing Conversational Negation](https://mlsanity.com/paper/2107.06820/) (2021)
- [Distilling Text into Circuits](https://mlsanity.com/paper/2301.10595/) (2023)
- [Language-independence of DisCoCirc's Text Circuits: English and Urdu](https://mlsanity.com/paper/2208.10281/) (2022)
- [A Pipeline For Discourse Circuits From CCG](https://mlsanity.com/paper/2311.17892/) (2023)
- [From Conceptual Spaces to Quantum Concepts: Formalising and Learning Structured Conceptual Models](https://mlsanity.com/paper/2401.08585/) (2023)
- [Quantum Algorithms for Compositional Text Processing](https://mlsanity.com/paper/2408.06061/) (2024)
- [A gentle introduction to Quantum Natural Language Processing](https://mlsanity.com/paper/2202.11766/) (2022)
- [Formalising and Learning a Quantum Model of Concepts](https://mlsanity.com/paper/2302.14822/) (2023)
- [Density Matrices for Metaphor Understanding](https://mlsanity.com/paper/2408.11846/) (2024)

## Abstract (arXiv)

We propose a framework to model an operational conversational negation by applying worldly context (prior knowledge) to logical negation in compositional distributional semantics. Given a word, our framework can create its negation that is similar to how humans perceive negation. The framework corrects logical negation to weight meanings closer in the entailment hierarchy more than meanings further apart. The proposed framework is flexible to accommodate different choices of logical negations, compositions, and worldly context generation. In particular, we propose and motivate a new logical negation using matrix inverse. We validate the sensibility of our conversational negation framework by performing experiments, leveraging density matrices to encode graded entailment information. We conclude that the combination of subtraction negation and phaser in the basis of the negated word yields the highest Pearson correlation of 0.635 with human ratings.