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        <title>NLP in Human Rights Research: Extracting Knowledge Graphs about Police and Army Units and Their Commanders</title>
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    <abstract>In this paper we explore the use of an NLP system to assist the work of Security Force Monitor (SFM). SFM creates data about the organizational structure, command personnel and operations of police, army and other security forces, which assists human rights researchers, journalists and litigators in their work to help identify and bring to account specific units and personnel alleged to have committed abuses of human rights and international criminal law. This paper presents an NLP system that extracts from English language news reports the names of security force units and the biographical details of their personnel, and infers the formal relationship between them. Published alongside this paper are the system’s code and training dataset. We find that the experimental NLP system performs the task at a fair to good level. Its performance is sufficient to justify further development into a live workflow that will give insight into whether its performance translates into savings in time and resource that would make it an effective technical intervention.</abstract>
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%0 Conference Proceedings
%T NLP in Human Rights Research: Extracting Knowledge Graphs about Police and Army Units and Their Commanders
%A Bauer, Daniel
%A Longley, Tom
%A Ma, Yueen
%A Wilson, Tony
%Y Pradhan, Sameer
%Y Kuebler, Sandra
%S Proceedings of the 16th Linguistic Annotation Workshop (LAW-XVI) within LREC2022
%D 2022
%8 June
%I European Language Resources Association
%C Marseille, France
%F bauer-etal-2022-nlp
%X In this paper we explore the use of an NLP system to assist the work of Security Force Monitor (SFM). SFM creates data about the organizational structure, command personnel and operations of police, army and other security forces, which assists human rights researchers, journalists and litigators in their work to help identify and bring to account specific units and personnel alleged to have committed abuses of human rights and international criminal law. This paper presents an NLP system that extracts from English language news reports the names of security force units and the biographical details of their personnel, and infers the formal relationship between them. Published alongside this paper are the system’s code and training dataset. We find that the experimental NLP system performs the task at a fair to good level. Its performance is sufficient to justify further development into a live workflow that will give insight into whether its performance translates into savings in time and resource that would make it an effective technical intervention.
%U https://aclanthology.org/2022.law-1.7
%P 62-69

Markdown (Informal)

[NLP in Human Rights Research: Extracting Knowledge Graphs about Police and Army Units and Their Commanders](https://aclanthology.org/2022.law-1.7) (Bauer et al., LAW 2022)

• NLP in Human Rights Research: Extracting Knowledge Graphs about Police and Army Units and Their Commanders (Bauer et al., LAW 2022)

ACL

• Daniel Bauer, Tom Longley, Yueen Ma, and Tony Wilson. 2022. NLP in Human Rights Research: Extracting Knowledge Graphs about Police and Army Units and Their Commanders. In Proceedings of the 16th Linguistic Annotation Workshop (LAW-XVI) within LREC2022, pages 62–69, Marseille, France. European Language Resources Association.