Argument Mining on Italian News Blogs

Abstract : The goal of argument mining is to extract structured information, namely the arguments and their relations, from un-structured text. In this paper, we propose an approach to argument relation prediction based on supervised learning of linguistic and semantic features of the text. We test our method on the CorEA corpus of user comments to online newspaper articles, evaluating our system's performances in assigning the correct relation, i.e., support or attack, to pairs of arguments. We obtain results consistently better than a sentiment analysis-based base-line (over two out three correctly classified pairs), and we observe that sentiment and lexical semantics are the most informative features with respect to the relation prediction task.
Type de document :
Communication dans un congrès
Third Italian Conference on Computational Linguistics (CLiC-it 2016) & Fifth Evaluation Campaign of Natural Language Processing and Speech Tools for Italian. Final Workshop (EVALITA 2016), Dec 2016, Naples, Italy
Liste complète des métadonnées

Littérature citée [16 références]  Voir  Masquer  Télécharger

https://hal.inria.fr/hal-01414698
Contributeur : Valerio Basile <>
Soumis le : lundi 12 décembre 2016 - 14:59:46
Dernière modification le : mardi 27 décembre 2016 - 15:41:30
Document(s) archivé(s) le : mardi 28 mars 2017 - 00:55:17

Fichier

paper8.pdf
Fichiers produits par l'(les) auteur(s)

Identifiants

  • HAL Id : hal-01414698, version 1

Collections

Citation

Pierpaolo Basile, Valerio Basile, Elena Cabrio, Serena Villata. Argument Mining on Italian News Blogs. Third Italian Conference on Computational Linguistics (CLiC-it 2016) & Fifth Evaluation Campaign of Natural Language Processing and Speech Tools for Italian. Final Workshop (EVALITA 2016), Dec 2016, Naples, Italy. 〈hal-01414698〉

Partager

Métriques

Consultations de
la notice

239

Téléchargements du document

103