# From syntactic structure to semantic relationship: hypernym extraction from definitions by recurrent neural networks using the part of speech information

arXiv: https://arxiv.org/abs/2012.03418 · HTML: https://mlsanity.com/paper/2012.03418/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 7 Dec 2020.

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

- [CoarSAS2hvec: Heterogeneous Information Network Embedding with Balanced Network Sampling](https://mlsanity.com/paper/2110.05820/) (2021)
- [Learning Semantic Text Similarity to rank Hypernyms of Financial Terms](https://mlsanity.com/paper/2303.13475/) (2023)

## Abstract (arXiv)

The hyponym-hypernym relation is an essential element in the semantic network. Identifying the hypernym from a definition is an important task in natural language processing and semantic analysis. While a public dictionary such as WordNet works for common words, its application in domain-specific scenarios is limited. Existing tools for hypernym extraction either rely on specific semantic patterns or focus on the word representation, which all demonstrate certain limitations.