NLAS-multi: A multilingual corpus of automatically generated Natural Language Argumentation Schemes

Ramon Ruiz-Dolz (Lead / Corresponding author), Joaquin Taverner, John Lawrence, Chris Reed

Research output: Contribution to journalArticlepeer-review

9 Downloads (Pure)

Abstract

Some of the major limitations identified in the areas of argument mining, argument generation, and natural language argument analysis are related to the complexity of annotating argumentatively rich data, the limited size of these corpora, and the constraints that represent the different languages and domains in which these data is annotated. To address these limitations, in this paper we present the following two contributions: an effective methodology for the automatic generation of natural language arguments in different topics and languages, and the largest publicly available corpus of Natural Language Argumentation Schemes available to date.

Original languageEnglish
Article number111087
Number of pages10
JournalData in Brief
Volume57
Early online date29 Oct 2024
DOIs
Publication statusPublished - Dec 2024

Keywords

  • Argument mining
  • Computational argumentation
  • Natural language generation

ASJC Scopus subject areas

  • General

Fingerprint

Dive into the research topics of 'NLAS-multi: A multilingual corpus of automatically generated Natural Language Argumentation Schemes'. Together they form a unique fingerprint.

Cite this