Wikibio: a Semantic Resource for the Intersectional Analysis of Biographical Events
This addresses a gap in digital humanities and bias analysis for minoritized groups, though it is incremental as it builds on existing corpora and tasks.
The paper tackled the lack of resources for biographical event detection by creating a new annotated corpus from 20 Wikipedia biographies and training a model that achieved an F-score of 0.808 for entity mentions and 0.859 for entity-related events.
Biographical event detection is a relevant task for the exploration and comparison of the ways in which people's lives are told and represented. In this sense, it may support several applications in digital humanities and in works aimed at exploring bias about minoritized groups. Despite that, there are no corpora and models specifically designed for this task. In this paper we fill this gap by presenting a new corpus annotated for biographical event detection. The corpus, which includes 20 Wikipedia biographies, was compared with five existing corpora to train a model for the biographical event detection task. The model was able to detect all mentions of the target-entity in a biography with an F-score of 0.808 and the entity-related events with an F-score of 0.859. Finally, the model was used for performing an analysis of biases about women and non-Western people in Wikipedia biographies.