# Neural relation extraction: a survey

arXiv: https://arxiv.org/abs/2007.04247 · HTML: https://mlsanity.com/paper/2007.04247/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 23 Jun 2020.

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

- [Clinical Relation Extraction Using Transformer-based Models](https://mlsanity.com/paper/2107.08957/) (2021)
- [Retrieval-Augmented Generation-based Relation Extraction](https://mlsanity.com/paper/2404.13397/) (2024)
- [Pre-trained Language Models as Re-Annotators](https://mlsanity.com/paper/2205.05368/) (2022)
- [Maximizing Relation Extraction Potential: A Data-Centric Study to Unveil Challenges and Opportunities](https://mlsanity.com/paper/2409.04934/) (2024)

## Abstract (arXiv)

Neural relation extraction discovers semantic relations between entities from unstructured text using deep learning methods. In this study, we present a comprehensive review of methods on neural network based relation extraction. We discuss advantageous and incompetent sides of existing studies and investigate additional research directions and improvement ideas in this field.