# INRIASAC: Simple Hypernym Extraction Methods

arXiv: https://arxiv.org/abs/1502.01271 · HTML: https://mlsanity.com/paper/1502.01271/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 4 Feb 2015.

## Built on by (most cited first, 3 of 3)

- [Hyperbolic Deep Neural Networks: A Survey](https://mlsanity.com/paper/2101.04562/) (2021)
- [Distilling Hypernymy Relations from Language Models: On the Effectiveness of Zero-Shot Taxonomy Induction](https://mlsanity.com/paper/2202.04876/) (2022)
- [Learning Semantic Text Similarity to rank Hypernyms of Financial Terms](https://mlsanity.com/paper/2303.13475/) (2023)

## Abstract (arXiv)

Given a set of terms from a given domain, how can we structure them into a taxonomy without manual intervention? This is the task 17 of SemEval 2015. Here we present our simple taxonomy structuring techniques which, despite their simplicity, ranked first in this 2015 benchmark. We use large quantities of text (English Wikipedia) and simple heuristics such as term overlap and document and sentence co-occurrence to produce hypernym lists. We describe these techniques and pre-sent an initial evaluation of results.