7 citations · 16 across the 14 of their papers we have counts for
6 papers · 1 filter
The Role of Natural Language Processing Tasks in Automatic Literary Character Network Construction
Arthur Amalvy, Vincent Labatut, Richard Dufour
The automatic extraction of character networks from literary texts is generally carried out using natural language processing (NLP) cascading pipelines. While this approach is wide…
Interconnected Kingdoms: Comparing 'A Song of Ice and Fire' Adaptations Across Media Using Complex Networks
Arthur Amalvy, Madeleine Janickyj, Shane Mannion +2
In this article, we propose and apply a method to compare adaptations of the same story across different media. We tackle this task by modelling such adaptations through character…
Annotation Guidelines for Corpus Novelties: Part 1 -- Named Entity Recognition
Arthur Amalvy, Vincent Labatut
The Novelties corpus is a collection of novels (and parts of novels) annotated for Named Entity Recognition (NER) among other tasks. This document describes the guidelines applied…
Annotation Guidelines for Corpus Novelties: Part 2 -- Alias Resolution Version 1.0
Arthur Amalvy, Vincent Labatut
The Novelties corpus is a collection of novels (and parts of novels) annotated for Alias Resolution, among other tasks. This document describes the guidelines applied during the an…
Whole-Graph Representation Learning For the Classification of Signed Networks
Noé Cecillon, Vincent Labatut, Richard Dufour +1
Graphs are ubiquitous for modeling complex systems involving structured data and relationships. Consequently, graph representation learning, which aims to automatically learn low-d…
Renard: A Modular Pipeline for Extracting Character Networks from Narrative Texts
Arthur Amalvy, Vincent Labatut, Richard Dufour
Renard (Relationships Extraction from NARrative Documents) is a Python library that allows users to define custom natural language processing (NLP) pipelines to extract character n…