# Relation Extraction from News Articles (RENA): A Tool for Epidemic Surveillance

arXiv: https://arxiv.org/abs/2311.01472 · HTML: https://mlsanity.com/paper/2311.01472/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 5 of its 7 references that are in the map.
- First posted on arXiv 31 Oct 2023.

## Builds on (most cited first, 5 of 5)

- [LLaMA: Open and Efficient Foundation Language Models](https://mlsanity.com/paper/2302.13971/) (2023)
- [QLoRA: Efficient Finetuning of Quantized LLMs](https://mlsanity.com/paper/2305.14314/) (2023)
- [Document-Level Relation Extraction with Reconstruction](https://mlsanity.com/paper/2012.11384/) (2020)
- [A Survey of Deep Learning Methods for Relation Extraction](https://mlsanity.com/paper/1705.03645/) (2017)
- [Survey of Text-based Epidemic Intelligence: A Computational Linguistic Perspective](https://mlsanity.com/paper/1903.05801/) (2019)

## Abstract (arXiv)

Relation Extraction from News Articles (RENA) is a browser-based tool designed to extract key entities and their semantic relationships in English language news articles related to infectious diseases. Constructed using the React framework, this system presents users with an elegant and user-friendly interface. It enables users to input a news article and select from a choice of two models to generate a comprehensive list of relations within the provided text. As a result, RENA allows real-time parsing of news articles to extract key information for epidemic surveillance, contributing to EPIWATCH, an open-source intelligence-based epidemic warning system.