# Uncovering Probabilistic Implications in Typological Knowledge Bases

arXiv: https://arxiv.org/abs/1906.07389 · HTML: https://mlsanity.com/paper/1906.07389/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 18 Jun 2019.

## Built on by (most cited first, 4 of 4)

- [Does Typological Blinding Impede Cross-Lingual Sharing?](https://mlsanity.com/paper/2101.11888/) (2021)
- [The Past, Present, and Future of Typological Databases in NLP](https://mlsanity.com/paper/2310.13440/) (2023)
- [Colexifications for Bootstrapping Cross-lingual Datasets: The Case of Phonology, Concreteness, and Affectiveness](https://mlsanity.com/paper/2306.02646/) (2023)
- [Patterns of Persistence and Diffusibility across the World's Languages](https://mlsanity.com/paper/2401.01698/) (2024)

## Abstract (arXiv)

The study of linguistic typology is rooted in the implications we find between linguistic features, such as the fact that languages with object-verb word ordering tend to have post-positions. Uncovering such implications typically amounts to time-consuming manual processing by trained and experienced linguists, which potentially leaves key linguistic universals unexplored. In this paper, we present a computational model which successfully identifies known universals, including Greenberg universals, but also uncovers new ones, worthy of further linguistic investigation. Our approach outperforms baselines previously used for this problem, as well as a strong baseline from knowledge base population.