# Renard: A Modular Pipeline for Extracting Character Networks from Narrative Texts

arXiv: https://arxiv.org/abs/2407.02284 · HTML: https://mlsanity.com/paper/2407.02284/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- Builds on 2 of its 10 references that are in the map.
- First posted on arXiv 2 Jul 2024.

## Builds on (most cited first, 2 of 2)

- [Extraction and Analysis of Fictional Character Networks: A Survey](https://mlsanity.com/paper/1907.02704/) (2019)
- [Analysis of a Play by Means of CHAPLIN, the Characters and Places Interaction Network Software](https://mlsanity.com/paper/1511.07001/) (2015)

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

- [GraphLit: Learning Text-Enriched Dynamic Character Network Representations for Literary Study](https://mlsanity.com/paper/2605.28643/) (2026)
- [Annotation Guidelines for Corpus Novelties: Part 2 -- Alias Resolution Version 1.0](https://mlsanity.com/paper/2410.00522/) (2024)
- [Annotation Guidelines for Corpus Novelties: Part 1 -- Named Entity Recognition](https://mlsanity.com/paper/2410.02281/) (2024)

## Abstract (arXiv)

Renard (Relationships Extraction from NARrative Documents) is a Python library that allows users to define custom natural language processing (NLP) pipelines to extract character networks from narrative texts. Contrary to the few existing tools, Renard can extract dynamic networks, as well as the more common static networks. Renard pipelines are modular: users can choose the implementation of each NLP subtask needed to extract a character network. This allows users to specialize pipelines to particular types of texts and to study the impact of each subtask on the extracted network.