Assisting Forensic Identification through Unsupervised Information Extraction of Free Text Autopsy Reports: The Disappearances Cases during the Brazilian Military Dictatorship

dc.contributor.affiliationUniversidade de Santiago de Compostela. Centro de Investigación en Tecnoloxías da Informacióngl
dc.contributor.authorMartín Rodilla, Patricia
dc.contributor.authorHattori, Marcia L.
dc.contributor.authorGonzález Pérez, César
dc.date.accessioned2020-11-26T11:45:54Z
dc.date.available2020-11-26T11:45:54Z
dc.date.issued2019
dc.description.abstractAnthropological, archaeological, and forensic studies situate enforced disappearance as a strategy associated with the Brazilian military dictatorship (1964–1985), leaving hundreds of persons without identity or cause of death identified. Their forensic reports are the only existing clue for people identification and detection of possible crimes associated with them. The exchange of information among institutions about the identities of disappeared people was not a common practice. Thus, their analysis requires unsupervised techniques, mainly due to the fact that their contextual annotation is extremely time-consuming, difficult to obtain, and with high dependence on the annotator. The use of these techniques allows researchers to assist in the identification and analysis in four areas: Common causes of death, relevant body locations, personal belongings terminology, and correlations between actors such as doctors and police officers involved in the disappearances. This paper analyzes almost 3000 textual reports of missing persons in São Paulo city during the Brazilian dictatorship through unsupervised algorithms of information extraction in Portuguese, identifying named entities and relevant terminology associated with these four criteria. The analysis allowed us to observe terminological patterns relevant for people identification (e.g., presence of rings or similar personal belongings) and automate the study of correlations between actors. The proposed system acts as a first classificatory and indexing middleware of the reports and represents a feasible system that can assist researchers working in pattern search among autopsy reportsgl
dc.description.peerreviewedSIgl
dc.description.sponsorshipThis research was partially funded by Spanish Ministry of Economy, Industry and 5 Competitiveness under its Competitive Juan de la Cierva Postdoctoral Research Programme, grant FJCI-2016-6 28032 and from the European Union, through the Marie Skłodowska-Curie Innovative Training Network ‘CHEurope: Critical Heritage Studies and the Future of Europe’ H2020 Marie Skłodowska-Curie Actions, grant 722416gl
dc.identifier.citationMartin-Rodilla, P.; Hattori, M.L.; Gonzalez-Perez, C. Assisting Forensic Identification through Unsupervised Information Extraction of Free Text Autopsy Reports: The Disappearances Cases during the Brazilian Military Dictatorship. Information 2019, 10, 231gl
dc.identifier.doi10.3390/info10070231
dc.identifier.essn2078-2489
dc.identifier.urihttp://hdl.handle.net/10347/23823
dc.language.isoenggl
dc.publisherMDPIgl
dc.relation.projectIDinfo:eu-repo/grantAgreement/EC/H2020/722416gl
dc.relation.publisherversionhttps://doi.org/10.3390/info10070231gl
dc.rights© 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/)gl
dc.rightsAtribución 4.0 Internacional
dc.rights.accessRightsopen accessgl
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.subjectInformation extractiongl
dc.subjectNamed entity recognitiongl
dc.subjectTerminology extractiongl
dc.subjectAutopsy reportsgl
dc.titleAssisting Forensic Identification through Unsupervised Information Extraction of Free Text Autopsy Reports: The Disappearances Cases during the Brazilian Military Dictatorshipgl
dc.typejournal articlegl
dc.type.hasVersionVoRgl
dspace.entity.typePublication
relation.isAuthorOfPublicationdd2f3302-92e1-4508-9658-5077376419fe
relation.isAuthorOfPublication.latestForDiscoverydd2f3302-92e1-4508-9658-5077376419fe

Files

Original bundle

Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
2019_information_martin_assisting.pdf
Size:
7.07 MB
Format:
Adobe Portable Document Format
Description: