Please use this identifier to cite or link to this item: https://hdl.handle.net/10216/171521
Author(s): Nikolaidis, Nikolaos
Stefanovitch, Nicolas
Silvano, Purificação
Stefanovitch, Nicolas
Guimarães, Nuno
Title: PolyNarrative: a multilingual, multilabel, multi-domain dataset for narrative extraction from news articles
Issue Date: 2025
Abstract: We present PolyNarrative, a new multilingual dataset of news articles, annotated for narra- tives. Narratives are overt or implicit claims, recurring across articles and languages, promot- ing a specific interpretation or viewpoint on an ongoing topic, often propagating mis/disinfor- mation. We developed two-level taxonomies with coarse- and fine-grained narrative labels for two domains: (i) climate change and (ii) the military conflict between Ukraine and Russia. We collected news articles in four languages (Bulgarian, English, Portuguese, and Russian) related to the two domains and manually anno- tated them at the paragraph level. We make the dataset publicly available, along with experi- mental results of several strong baselines that assign narrative labels to news articles at the paragraph or the document level. We believe that this dataset will foster research in narrative detection and enable new research directions to- wards more multi-domain and highly granular narrative related tasks.
Subject: Linguística
Linguistics
URI: https://hdl.handle.net/10216/171521
Source: Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
Document Type: Artigo em Livro de Atas de Conferência Internacional
Rights: openAccess
Appears in Collections:FEUP - Artigo em Livro de Atas de Conferência Internacional
FLUP - Artigo em Livro de Atas de Conferência Internacional

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