W iki B io: a Semantic Resource for the Intersectional Analysis of Biographical Events (2023)

Abstract: Biographical event detection is a relevant task that allows for the exploration and comparison of the ways in which people’s lives are told and represented. This may support several real-life 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 aligned with 5 existing corpora in order 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.

## introduction detecting biographical events from unstructured data is a relevant task to explore and compare bias in representations of individuals. in recent years, the interest in this topic has been favored by studies about social biases on allegedly objective public archives such as wikipedia. @xcite developed a resource for investigating gender bias on wikipedia biographies showing that personal life events tend to be more frequent in female career sections than in those of men. @xcite developed bert-based contextualized embeddings for exploring representations of women on wikipedia and reddit. the detection of biographical events has been addressed with complementary approaches by different research communities. projects in digital humanities have focused mostly on representational aspects, delivering ontologies and knowledge graphs for the collection and study of biographical events @xcite @xcite . when it comes to nlp, the focus has been mainly on developing models for the detection and classification of events @xcite . few are the works that directly target biographies and focus on identifying biographical events with varied approaches (supervised and unsupervised) across different datasets (e.g., wikipedia vs. newspaper articles), making their comparison impossible @xcite @xcite . although not directly targeting biographies, some works focused on the identification of entity-related sequences of events @xcite and entity-based storylines @xcite @xcite . despite the above mentioned variety of approaches to biographical event detection, there are pending and urgent issues to be addressed, which limit a full development of the research area. in particular, we have identified three critical issues: i) the lack of a benchmark annotated corpus for evaluating biographical event detection; ii) the lack of models specifically designed for detecting and extracting biographical events; and finally iii) the lack of a systematic study of the potential representation bias of minority groups, non-western people, and younger generations in biography repositories publicly available, such as wikipedia (d'ignazio and @xcite ). contributions our work addresses these issues by presenting a novel benchmark corpus, a bertbased model for biographical event detection, and an analysis of 48, 789 wikipedia biographies of writers born since 1808. our results show that existing data sets annotated for event detection may be easily re-used to detect biographical events achieving good results in terms of f-measure. the analysis of the 48, 789 biographies from wikipedia extends the findings from previous work indicating that representational biases are present in an allegedly objective source such as wikipedia along intersectional axes @xcite , namely ethnicity and gender. the rest of the paper is organized as follows. in section 2, we present wikibio, a novel manually annotated corpus of biographical events. section 3 presents the experiments in event detection and coreference resolution of the target entities of a biographies. section 4 is devoted to the analysis of the biases in wikipedia biographies. conclusions and future work end the paper in section 5. code and wikibio corpus are available at the following url: https://github.com/ marcostranisci/wikibio/ . ## the wikibio corpus wikibio is a corpus annotated for biographical event detection, composed of 20 wikipedia biographies. the corpus includes all the events which are associated with the entity target of the biography. in this section, we present our annotation scheme, discuss the agreement scores and present some cases of disagreement. lastly, we present the results of our annotation effort, and compare them with existing corpora annotated for event detection and coreference resolution. ## detecting biographical events in this section we describe a series of experiments for the detection of biographical events. experiments involve the use of the existing annotated corpora for two tasks: entity mentions detection (section 3.1) and event detection (section 3.2). in both cases we used a 66 million parameters distil-bert model @xcite . in this setting the wikibio corpus is both used as part of the training set and as a benchmark for testing how well existing annotated corpora may be used for the task. for such experiments a nvidia rtx 3030 ti was used. the average length of each fine-tuning session was 40 minutes. ## an intersectional analysis of wikipedia biographies in this section we provide an analysis of writers' biographies on wikipedia adopting intersectionality as a theoretical framework and the model described in section 3 as a tool for detecting biographical events. the concept of intersectionality @xcite 2017 ) has been developed in the context of gender and black studies to account inequalities that cannot be explained without a joint analysis of socio-demographic factors. for instance, african american women workers suffer higher discrimination than their male counterpart, as @xcite observed in her seminal work. therefore, the injection of different socio-demographic features for the analysis of discriminations may unfold hidden forms of inequities about certain segments of population. we adopt this framework to analyse how the representations of non-western women writers on wikipedia differs from those of western women, transnational men, and western men. for this analysis, we gathered 48, 486 wikipedia biographies of writers born since 1808. we define as transnational all the writers born outside western countries and people who belong to ethnic minorities @xcite . western men's biographies are 28, 036, western women's 12, 413, transnational men's 5, 471, and transnational women's 2, 470. information about occupation, gender, year of birth, ethnic group, and country of birth was obtained from wikidata (vrandečić and krötzsch, 2014), which has been used for filtering and classifying biographies. for each biography, we first identified all the mentions of the corresponding target entity (section 3.1). we then removed the sentences that do not contain a mention of the entity. this reduced the number of sentences to be annotated for event detection from 1, 486, 320 to 1, 163, 475 (-21.8%). as a final step, we annotated events (section 3.2) in the filtered sentences. the analysis of event types presents a similar distribution. 27, 885 event types -intended as the number of unique tokens that occur in each distribution -are detected in western men's biographies (44.9 per biography), while only 9, 254 in transnational women's biographies (40.4 per biography). however, the overlap of event types between these two categories is very large (92.6%) the same comparison, conducted on the other groups, reveals a higher number of group-specific event types: 87.8% of event types about transnational men are shared with western men, and the rate is lower for western women (84.1%). a comparative analysis of most distinctive events per category of people provides additional insight about the representation of women and transnational writers in wikipedia biographies. in order to do so, we first computed the average frequency of each event in all biographies of the four groups of writers in a first insight from a general overview of distinctive events about transnational women writers is that they seem to never die. events like 'death' or 'died' are never distinctive for them but always for the group against which they are compared. this may be explained by the average year of birth of transnational women writers with a biography on wikipedia, which is 1951, while for western men is 1936, 1943 for transnational men, and 1944 for western woman. ## conclusion and future work in this paper we presented a novel set of computational resources for deepening the analysis of biographical events and improving their automatic detection. we found that existing annotated corpora may be successfully reused to train models that obtain good performances. the model for entity detection, trained on ontonotes, obtained a fscore of 0.808, while the model for event detection, trained on timebank and wikibio, scored 0.859. we have applied these newly developed resources to perform an analysis of biases in transnational women writers on wikipedia adopting intersectionality as a framework to interpret our results. in particular, we have identified that the representation of women and non-western people on wikipedia is problematic and biased. using different axes of analysis -as suggested by intersectionality -it becomes easier to better identify these biases. for instance, gender bias against transnational women are more marked when comparing their biographies against those of transnational men rather than western ones. on the other hand, potential racial biases emerge when comparing transnational women to western women. using an intersectional framework would benefit the understanding and countering of biases of women and non-western people on wikipedia. future work will improve the model for biographical event detection, and to extend the analysis on a wider set of biographical entries from different sources.