# Guidelines and a Corpus for Extracting Biographical Events

arXiv: https://arxiv.org/abs/2206.03547 · HTML: https://mlsanity.com/paper/2206.03547/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- Builds on 3 of its 30 references that are in the map.
- First posted on arXiv 7 Jun 2022.

## Builds on (most cited first, 3 of 3)

- [Simple BERT Models for Relation Extraction and Semantic Role Labeling](https://mlsanity.com/paper/1904.05255/) (2019)
- [Men Are Elected, Women Are Married: Events Gender Bias on Wikipedia](https://mlsanity.com/paper/2106.01601/) (2021)
- [AceKG: A Large-scale Knowledge Graph for Academic Data Mining](https://mlsanity.com/paper/1807.08484/) (2018)

## Built on by (most cited first, 2 of 2)

- [The URW-KG: a Resource for Tackling the Underrepresentation of non-Western Writers](https://mlsanity.com/paper/2212.13104/) (2022)
- [Supernova Event Dataset: Interpreting Large Language Models' Personality through Critical Event Analysis](https://mlsanity.com/paper/2506.12189/) (2025)

## Abstract (arXiv)

Despite biographies are widely spread within the Semantic Web, resources and approaches to automatically extract biographical events are limited. Such limitation reduces the amount of structured, machine-readable biographical information, especially about people belonging to underrepresented groups. Our work challenges this limitation by providing a set of guidelines for the semantic annotation of life events. The guidelines are designed to be interoperable with existing ISO-standards for semantic annotation: ISO-TimeML (ISO-24617-1), and SemAF (ISO-24617-4). Guidelines were tested through an annotation task of Wikipedia biographies of underrepresented writers, namely authors born in non-Western countries, migrants, or belonging to ethnic minorities. 1,000 sentences were annotated by 4 annotators with an average Inter-Annotator Agreement of 0.825. The resulting corpus was mapped on OntoNotes. Such mapping allowed to to expand our corpus, showing that already existing resources may be exploited for the biographical event extraction task.