Cross-Lingual Annotation Projection for Argument Mining in Portuguese

• Type: Article in International Conference Proceedings Book
• Date: 2021

Authors

Afonso Sousa (Author) Other; Bernardo Leite (Author) Other; Gil Rocha (Author) Other; Henrique Lopes Cardoso (Author) FEUP

Conference proceedings International

Title: PROGRESS IN ARTIFICIAL INTELLIGENCE (EPIA 2021)

Pages: 752-765

20th EPIA Conference on Artificial Intelligence (EPIA)

ELECTR NETWORK, SEP 07-09, 2021

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Other information

Authenticus ID: P-00V-CPF

DOI: 10.1007/978-3-030-86230-5_59

Abstract (EN): While Argument Mining has seen increasing success in monolingual settings, especially for the English language, other less-resourced languages are still lagging behind. In this paper, we build a Portuguese projected version of the Persuasive Essays corpus and evaluate it both intrinsically (through backprojection) and extrinsically (in a sequence tagging task). To build the corpus, we project the token-level annotations into a new Portuguese version using translations and respective alignments. Intrinsic evaluation entails rebuilding the English corpus using back alignment and back projection from the Portuguese version, comparing against the original English annotations. For extrinsic evaluation, we assess and compare the performance of machine learning models on several language variants of the corpus (including the Portuguese one), following both inlanguage/projection training and direct transfer. Our evaluation highlights the quality of the generated corpus. Experimental results show the effectiveness of the projection approach, while providing competitive baselines for the Portuguese version of the corpus. The corpus and code are available (https://github.com/ AfonsoSalgadoSousa/argumentation mining pt).

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 14