Work

The revision of linguistic annotation in the Universal Dependencies framework: a look at the annotators’ behavior

Year: 2025

Type: conference-paper

Abstract: This paper presents strategies to revise an automatically annotated corpus according to the Universal Dependencies framework and discusses the learned lessons, mainly regarding the annotators' behavior.The revision strategies are not relying on examples from any specific language and, because they are languageindependent, can be adopted in any language and corpus annotation initiative.

Source: Linguistic Annotation Workshop

DOI: 10.18653/v1/2025.law-1.5

Authors: Magali Sanches Duran, Lucelene Lopes, Thiago Alexandre Salgueiro Pardo

Institution: Universidade de São Paulo

Language: English

Topic: Natural Language Processing Techniques

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: hybrid

Funders: International Business Machines Corporation, Fundação de Amparo à Pesquisa do Estado de São Paulo, Ministério da Ciência, Tecnologia e Inovação, Universidade de São Paulo

Awards: G295657101, Center for Artificial Intelligence, G5848565654