# Graphene: A Context-Preserving Open Information Extraction System

arXiv: https://arxiv.org/abs/1808.09463 · HTML: https://mlsanity.com/paper/1808.09463/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 28 Aug 2018.

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

- [Context-Preserving Text Simplification](https://mlsanity.com/paper/2105.11178/) (2021)
- [Common Sense Knowledge Learning for Open Vocabulary Neural Reasoning: A First View into Chronic Disease Literature](https://mlsanity.com/paper/2111.13781/) (2021)
- [SocraticKG: Knowledge Graph Construction via QA-Driven Fact Extraction](https://mlsanity.com/paper/2601.10003/) (2026)

## Abstract (arXiv)

We introduce Graphene, an Open IE system whose goal is to generate accurate, meaningful and complete propositions that may facilitate a variety of downstream semantic applications. For this purpose, we transform syntactically complex input sentences into clean, compact structures in the form of core facts and accompanying contexts, while identifying the rhetorical relations that hold between them in order to maintain their semantic relationship. In that way, we preserve the context of the relational tuples extracted from a source sentence, generating a novel lightweight semantic representation for Open IE that enhances the expressiveness of the extracted propositions.