mlsanityData to 14 Oct 2026

Named-Entity Recognition in the Crime Domain (CrimeNER): Case Study and Dataset

arXiv 2603.02150 ↗First posted 2 Mar 2026cs.CL cs.AI cs.DBcited by 2

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Abstract (arXiv)

The extraction of critical information from crime-related documents is a crucial task for law enforcement agencies. The extraction of this information can be interpreted as a Named-Entity Recognition (NER) task. However, there is a considerable lack of adequately annotated data on general real-world crime scenarios. To address this issue, we present CrimeNER, a case study of crime-related NER, and a general crime-related Named-Entity Recognition database (CrimeNER-db), consisting of more than 1.5K annotated documents extracted from public reports of terrorist attacks and the US Department of Justice's press notes. We define 4 coarse types of crime entity and 21 fine-grained entity types. We address the quality of the presented database with experiments using fully supervised finetuned general NER models and zero- and few-shot experiments to address the generalization capabilities. The database is available on GitHub.

Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). Builds on 14 of its 35 references that are in the map. First posted on arXiv 2 Mar 2026.

Builds on

14 of 35 references.

References · 14

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  10. 2021Few-NERD: A Few-Shot Named Entity Recognition Datasetcited by 152
  11. 2022E-NER -- An Annotated Named Entity Recognition Corpus of Legal Textcited by 13
  12. 2025Benchmarking Graph Neural Networks for Document Layout Analysis in Public Affairscited by 7
2 more
  1. 2025Privacy-Aware Detection of Fake Identity Documents: Methodology, Benchmark, and Improved Algorithms (FakeIDet2)cited by 7
  2. 2025Knowledge Acquisition on Mass-shooting Events via LLMs for AI-Driven Justicecited by 1

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2026: 2.

2 papers.

  1. 2026Comparative Study of Domain-adapted VLMs for General Document Visual Question Answeringcited by 3
  2. 2026CrimeNER Demo: Named-Entity Recognition in the Crime Domaincited by 0