{"id":30183616,"url":"https://github.com/dmis-lab/law-and-order","last_synced_at":"2025-08-12T11:15:06.401Z","repository":{"id":292593218,"uuid":"981359150","full_name":"dmis-lab/Law-and-Order","owner":"dmis-lab","description":null,"archived":false,"fork":false,"pushed_at":"2025-05-16T07:15:09.000Z","size":73,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":2,"default_branch":"main","last_synced_at":"2025-07-18T04:44:42.493Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":null,"language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/dmis-lab.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null,"zenodo":null}},"created_at":"2025-05-10T23:28:38.000Z","updated_at":"2025-05-16T07:15:13.000Z","dependencies_parsed_at":"2025-05-11T00:35:27.384Z","dependency_job_id":null,"html_url":"https://github.com/dmis-lab/Law-and-Order","commit_stats":null,"previous_names":["dmis-lab/law-and-order"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/dmis-lab/Law-and-Order","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/dmis-lab%2FLaw-and-Order","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/dmis-lab%2FLaw-and-Order/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/dmis-lab%2FLaw-and-Order/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/dmis-lab%2FLaw-and-Order/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/dmis-lab","download_url":"https://codeload.github.com/dmis-lab/Law-and-Order/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/dmis-lab%2FLaw-and-Order/sbom","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":270048482,"owners_count":24518075,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","status":"online","status_checked_at":"2025-08-12T02:00:09.011Z","response_time":80,"last_error":null,"robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":true,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":[],"created_at":"2025-08-12T11:15:02.166Z","updated_at":"2025-08-12T11:15:06.387Z","avatar_url":"https://github.com/dmis-lab.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Law \u0026 Order\nBenchmark Dataset for Evaluating Large Language Models in Policing\n\n## Contributors\n\n\u003ctable\u003e\n\t\u003ctr\u003e\n\t\t\u003cth\u003eName\u003c/th\u003e\t\t\n\t\t\u003cth\u003eAffiliation\u003c/th\u003e\n\t\t\u003cth\u003eEmail\u003c/th\u003e\n\t\u003c/tr\u003e\n\t\u003ctr\u003e\n\t\t\u003ctd\u003eHeedou Kim\u003c/td\u003e\t\t\n\t\t\u003ctd\u003eKorean National Police Agency\u003cbr\u003e Data Mining and Information Systems Lab,\u003cbr\u003eKorea University, South Korea\u003c/td\u003e\n\t\t\u003ctd\u003eheedou123@korea.ac.kr\u003c/td\u003e\n\t\u003c/tr\u003e\n  \u003ctr\u003e\n\t\t\u003ctd\u003eMogan Gim\u003c/td\u003e\t\t\n\t\t\u003ctd\u003eDepartment of Biomedical Engineering,\u003cbr\u003eHankuk University of Foreign Studies, South Korea\u003c/td\u003e\n\t\t\u003ctd\u003egimmogan@hufs.ac.kr\u003c/td\u003e\n\t\u003c/tr\u003e\n \t\u003ctr\u003e\n\t\t\u003ctd\u003eDonghee Choi\u003c/td\u003e\t\t\n\t\t\u003ctd\u003eDepartment of Metabolism, Digestion and Reproduction, \u003cbr\u003eImperial College London, United Kingdom\u003c/td\u003e\n\t\t\u003ctd\u003edonghee.choi@imperial.ac.uk\u003c/td\u003e\n\t\u003c/tr\u003e\n   \t\u003ctr\u003e\n\t\t\u003ctd\u003eSoonil Bae\u003c/td\u003e\t\t\n\t\t\u003ctd\u003ePolice Science Institute, \u003cbr\u003eKorea National Police University, South Korea\u003c/td\u003e\n\t\t\u003ctd\u003esoonil.bae@police.go.kr\u003c/td\u003e\n\t\u003c/tr\u003e\n   \t\u003ctr\u003e\n\t\t\u003ctd\u003eMiyoung Kim*\u003c/td\u003e\t\t\n\t\t\u003ctd\u003eDepartment of Computing Science, \u003cbr\u003eUniversity of Alberta, Canada\u003c/td\u003e\n\t\t\u003ctd\u003emiyoung2@ualberta.ca\u003c/td\u003e\n\t\u003c/tr\u003e\n\t\u003ctr\u003e\n\t\t\u003ctd\u003eJaewoo Kang*\u003c/td\u003e\t\t\n\t\t\u003ctd\u003eData Mining and Information Systems Lab,\u003cbr\u003eKorea University, South Korea\u003c/td\u003e\n\t\t\u003ctd\u003ekangj@korea.ac.kr\u003c/td\u003e\n\t\u003c/tr\u003e\n\u003c/table\u003e\n\n- \u0026ast;: *Corresponding Author*\n\n# How to Use Dataset\n\n```python\nfrom datasets import load_dataset\n\n# Criminal Hypothesis\nds = load_dataset(\"PSI-PAIRC/Law_and_Order\", name=\"CI_Criminal_Hypothesis\")\n\nprint(ds[\"train\"][0])     \nprint(ds[\"validation\"][0])  \nprint(ds[\"test\"][0])        \n\n# Statute_Mapping \nds = load_dataset(\"PSI-PAIRC/Law_and_Order\", name=\"CI_Statute_Mapping\")\n\n# Element_Analysis \nds = load_dataset(\"PSI-PAIRC/Law_and_Order\", name=\"CI_Element_Analysis\")\n\n# Fradulent_Intention_Interpretation \nds = load_dataset(\"PSI-PAIRC/Law_and_Order\", name=\"IA_Fradulent_Intention_Interpretation\")\n\n# Fradulent_Scenario_Completion \nds = load_dataset(\"PSI-PAIRC/Law_and_Order\", name=\"IA_Fradulent_Scenario_Completion\")\n\n# Case_Analysis_NER \nds = load_dataset(\"PSI-PAIRC/Law_and_Order\", name=\"IA_Case_Analysis_NER\")\n\n# Deceptive_Message_Analysis \nds = load_dataset(\"PSI-PAIRC/Law_and_Order\", name=\"IA_Deceptive_Message_Analysis\")\n\n# Offense_Detection \nds = load_dataset(\"PSI-PAIRC/Law_and_Order\", name=\"PO_Offense_Detection\")\n\n# Operational_QA \nds = load_dataset(\"PSI-PAIRC/Law_and_Order\", name=\"PO_Operational_QA\")\n\n# Emergency_Reports_Summarization \nds = load_dataset(\"PSI-PAIRC/Law_and_Order\", name=\"PT_Emergency_Reports_Summarization\")\n\n```\n\n\n## Link to Dataset\nhttps://huggingface.co/datasets/PSI-PAIRC/Law_and_Order\n\n# Benchmarks\n\n| LLM as                | Task                                | Metric            | GPT4o | Gemini 2.0 | EEVE 10.8B | SOLAR 10.7B | Llama 3.1-8B | Llama 3.2-1B |\n|-----------------------|-------------------------------------|-------------------|--------|--------------|--------------|---------------|----------------|----------------|\n| Police Officer        | Operational QA                      | LLM-as-a-Judge    | 0.69   | 0.66         | 0.87         | 0.85          | 0.88           | 0.64           |\n|                       | Offense Detection                   | ACC               | 0.86   | 0.86         | 0.87         | 0.98          | 0.50           | 0.21           |\n|                       |                                     | F1                | 0.90   | 0.93         | 0.95         | 0.99          | 0.77           | 0.61           |\n| Intelligence Analyst  | Fraudulent Scenario Detection       | ACC               | 0.97   | 0.87         | 0.99         | 0.99          | 0.86           | 0.63           |\n|                       |                                     | F1                | 0.97   | 0.88         | 0.99         | 0.99          | 0.85           | 0.58           |\n|                       | Fraudulent Scenario Completion      | LLM-as-a-Judge    | 0.70   | 0.66         | 0.67         | 0.71          | 0.71           | 0.64           |\n|                       | Fraudulent Intention Interpretation | ACC               | 0.11   | 0.16         | 0.19         | 0.14          | 0.14           | 0.04           |\n|                       |                                     | F1 (micro)        | 0.51   | 0.79         | 0.64         | 0.47          | 0.56           | 0.27           |\n|                       | Deceptive Message Analysis          | ACC               | 0.88   | 0.93         | 0.97         | 0.99          | 0.97           | 0.88           |\n|                       |                                     | F1 (macro)        | 0.70   | 0.76         | 0.91         | 0.98          | 0.95           | 0.73           |\n|                       |                                     | F1 (micro)        | 0.88   | 0.93         | 0.97         | 0.99          | 0.97           | 0.88           |\n|                       | Case Analysis NER                   | Precision         | 0.17   | 0.14         | 0.31         | 0.52          | 0.17           | 0.08           |\n|                       |                                     | F1 (macro)        | 0.17   | 0.14         | 0.22         | 0.29          | 0.16           | 0.06           |\n|                       |                                     | F1 (micro)        | 0.46   | 0.44         | 0.06         | 0.11          | 0.04           | 0.03           |\n|                       |                                     | F1 (weighted avg) | 0.51   | 0.49         | 0.26         | 0.42          | 0.22           | 0.11           |\n| Patrol Officer        | Emergency Reports Summarization     | LLM-as-a-Judge    | 0.89   | 0.75         | 0.62         | 0.56          | 0.51           | 0.20           |\n| Criminal Investigator | Criminal Hypothesis                 | ACC               | 0.73   | 0.62         | 0.74         | 0.62          | 0.62           | 0.62           |\n|                       |                                     | F1                | 0.79   | 0.77         | 0.79         | 0.77          | 0.77           | 0.77           |\n|                       | Statute Mapping                     | ACC               | 0.43   | 0.40         | 0.86         | 0.88          | 0.19           | 0.07           |\n|                       |                                     | F1                | 0.65   | 0.69         | 0.92         | 0.95          | 0.35           | 0.12           |\n|                       | Element Analysis                    | ACC               | 0.67   | 0.81         | 0.66         | 0.71          | 0.64           | 0.12           |\n|                       |                                     | F1                | 0.84   | 0.93         | 0.81         | 0.88          | 0.82           | 0.24           |\n\n# Licensing Information\nLicensed under the CC BY-NC 4.0\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdmis-lab%2Flaw-and-order","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fdmis-lab%2Flaw-and-order","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdmis-lab%2Flaw-and-order/lists"}