# Extracting Core Claims from Scientific Articles

arXiv: https://arxiv.org/abs/1707.07678 · HTML: https://mlsanity.com/paper/1707.07678/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 24 Jul 2017.

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

- [SciTweets -- A Dataset and Annotation Framework for Detecting Scientific Online Discourse](https://mlsanity.com/paper/2206.07360/) (2022)
- [Monitoring Transformative Technological Convergence Through LLM-Extracted Semantic Entity Triple Graphs](https://mlsanity.com/paper/2510.25370/) (2025)
- [Context Selection for Hypothesis and Statistical Evidence Extraction from Full-Text Scientific Articles](https://mlsanity.com/paper/2603.21193/) (2026)

## Abstract (arXiv)

The number of scientific articles has grown rapidly over the years and there are no signs that this growth will slow down in the near future. Because of this, it becomes increasingly difficult to keep up with the latest developments in a scientific field. To address this problem, we present here an approach to help researchers learn about the latest developments and findings by extracting in a normalized form core claims from scientific articles. This normalized representation is a controlled natural language of English sentences called AIDA, which has been proposed in previous work as a method to formally structure and organize scientific findings and discourse. We show how such AIDA sentences can be automatically extracted by detecting the core claim of an article, checking for AIDA compliance, and - if necessary - transforming it into a compliant sentence. While our algorithm is still far from perfect, our results indicate that the different steps are feasible and they support the claim that AIDA sentences might be a promising approach to improve scientific communication in the future.