Work

Discourse annotation guideline for low-resource languages

Year: 2025

Type: article

Abstract: Most existing discourse annotation guidelines have focused on the English language. As a result, there is a significant lack of research and resources concerning computational discourse-level language understanding and generation for other languages. To fill this relevant gap, we introduce the first discourse annotation guideline using the rhetorical structure theory (RST) for low-resource languages. Specifically, this guideline provides accurate examples of discourse coherence relations in three romance languages: Italian, Portuguese, and Spanish. We further discuss theoretical definitions of RST and compare different artificial intelligence discourse frameworks, hence offering a reliable and accessible survey to new researchers and annotators.

Source: Natural language processing.

DOI: 10.1017/nlp.2024.19

Authors: Francielle Vargas, Wolfgang Schmeisser-Nieto, Zohar Rabinovich, Thiago A. S. Pardo, Fabrício Benevenuto

Institutions: Universidade de São Paulo, Universitat de Barcelona, University of Southern California, Universidade Federal de Minas Gerais

Language: English

Topic: Natural Language Processing Techniques

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: hybrid

Estimated APC paid: $3,550

OpenAlex ID: W4408039981

FWCI: 0.408

Cites:

Cited by: 1

Related to: 10