# On the Distinctive Co-occurrence Characteristics of Antonymy

arXiv: https://arxiv.org/abs/2509.11534 · HTML: https://mlsanity.com/paper/2509.11534/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- Builds on 3 of its 27 references that are in the map.
- First posted on arXiv 15 Sep 2025.

## Builds on (most cited first, 3 of 3)

- [HyperLex: A Large-Scale Evaluation of Graded Lexical Entailment](https://mlsanity.com/paper/1608.02117/) (2016)
- [Hearst Patterns Revisited: Automatic Hypernym Detection from Large Text Corpora](https://mlsanity.com/paper/1806.03191/) (2018)
- [Misalignment of Semantic Relation Knowledge between WordNet and Human Intuition](https://mlsanity.com/paper/2412.02138/) (2024)

## Built on by (most cited first, 2 of 2)

- [Relation Geometry in Semantic Space of Language Models](https://mlsanity.com/paper/2607.26762/) (2026)
- [Evaluating Semantic Relation Knowledge through Bidirectional Relation Prediction from Gloss Pairs](https://mlsanity.com/paper/2610.14442/) (2026)

## Abstract (arXiv)

Antonymy has long received particular attention in lexical semantics. Previous studies have shown that antonym pairs frequently co-occur in text, across genres and parts of speech, more often than would be expected by chance. However, whether this co-occurrence pattern is distinctive of antonymy remains unclear, due to a lack of comparison with other semantic relations. This work fills the gap by comparing antonymy with three other relations across parts of speech using robust co-occurrence metrics. We find that antonymy is distinctive in three respects: antonym pairs co-occur with high strength, in a preferred linear order, and within short spans. All results are available online.