Digging into Human Rights Violations: Anaphora Resolution and Emergent Witnesses

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Digging into Human Rights Violations will develop methods and tools for discovering and visualizing the stories of hidden victims and unidentified perpetrators in collections of human rights violations reports and witness statements. This research in natural language processing is necessary because, a) collections documenting human rights violations frequently number many tens of thousands to tens of millions of documents, a scale that conceals victim, violation, and violator; b) many victim?s stories are only present as fragments in the reports and accounts of observers and survivors; and c) current tools excel at searching, not reading. This project's computational reader, developed using collections compiled for various Truth and Reconciliation and Historical Clarification Committees, will consist of an engine for reconstructing stories from fragments scattered across a collection, and an interface for navigating those compiled stories and the documents from which they come. Although developed for use by investigators and prosecutors of human rights violations, this novel tool will expand the possibilities of text mining and will be generally useful for scholars, researchers, and practitioners with a need to track entities, events, and patterns across large document collections. The key development is to further work on anaphora resolution (where anaphora is the existence of an expression referring to another -- usually a pronoun to its antecedent). In some cases identifying anaphora relatively straightforward, but in many cases it presents a significant challenge to traditional natural language processing methods. This project will involve a combination of natural language processing and qualitative language analysis.This project's broader impacts lie in its clear potential to inform scholars and government officials working on issues of human rights and in truth and reconciliation contexts. Further, the project includes significant student training, including training in interdisciplinary research methods.This grant was made as part of the Digging Into Data Challenge, an international competition designed to foster research collaboration across countries and to encourage innovative approaches to analyzing large data sets in the social sciences and humanities. The US based researchers will collaborate with scholars in Canada to achieve the goals of this project.