Datasets:
Add task_categories to dataset card
#2
by nielsr HF Staff - opened
README.md
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data_files: tables/
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data_files: tables/
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data_files:
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data_files: schema_audit/
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| `schema_audit/` (
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}
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---
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language:
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- en
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license: cc-by-nc-sa-4.0
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size_categories:
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- 10K<n<100K
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pretty_name: 'SitrepGap: Operational Completeness and Grounding of LLM Situation Reports'
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task_categories:
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- text-classification
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tags:
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- crisis-informatics
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- situation-reports
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- llm-evaluation
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- llm-as-a-judge
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- humanitarian
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configs:
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- config_name: judgements
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data_files: per_judgement.csv
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default: true
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- config_name: human_validation
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data_files: tables/human_validation_pairs.csv
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- config_name: slot_coverage
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data_files: tables/slot_coverage_by_judge_arm.csv
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- config_name: completeness_by_document
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data_files: tables/completeness_by_document.csv
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- config_name: reliefweb_manifest
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data_files: reliefweb_report_manifest.csv
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- config_name: humaid_manifest
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data_files: humaid_source_manifest.csv
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- config_name: machine_report_manifest
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data_files: machine_report_manifest.csv
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- config_name: matcher_audit
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data_files: matcher_audit.csv
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- config_name: open_codes
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data_files: schema_audit/open_codes.csv
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- config_name: clusters
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data_files: schema_audit/clusters_summary.csv
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---
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# crisis-sitrep-eval
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Evaluation resources for comparing LLM-generated and professional humanitarian situation
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reports (sitreps), from "Looking Complete Is Not Being Grounded: Evaluating LLM Sitreps Against
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Human-Authored Situation Reports" (LT4CPR Workshop @ AACL-IJCNLP 2026).
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- Paper: https://arxiv.org/abs/2610.18762
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- Code: https://github.com/techsachinkr/llm-sitrep-evaluation
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## Contents
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| File | What it holds |
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|---|---|
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| `frozen_schema.yaml` | The 15-slot information schema, with definitions and two synthetic examples per slot |
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| `per_judgement.csv` (`judgements`) | Slot-level judge verdicts (ABSENT / PARTIAL / PRESENT) for 121 professional and 261 LLM-generated reports across five disasters, without text |
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| `tables/human_validation_pairs.csv` (`human_validation`) | 100 blind human labels with the four judges' verdicts (Cyclone Idai) |
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| `tables/` | Every table behind the paper's numbers: completeness, slot coverage, figure grounding, source availability, metric correlations, sensitivity analyses |
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| `reliefweb_report_manifest.csv` | Titles, organisations, dates, URLs and hashes of the 125 ReliefWeb reports |
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| `humaid_source_manifest.csv` | HumAID tweet IDs and text hashes (76,484 rows) |
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| `machine_report_manifest.csv` | Request hash, output hash, call time and model ID for each of the 264 generations |
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| `prompts.json`, `measurement_spec.json`, `model_roles.csv`, `decoding_parameters.csv` | Prompts, measurement rules, models and decoding settings |
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| `schema_audit/open_codes.csv` (`open_codes`) | All 1,360 open codes by report (name, definition, confidence, cluster), without evidence spans |
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| `schema_audit/clusters_summary.csv` (`clusters`), `schema_audit/clusters.csv` | All 382 clusters (threshold .35), ranked, with the 25 candidates flagged and every member code |
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| `schema_audit/` (other files) | Induction sample, the 25 candidates, merge decisions and rationales, review record, frozen schema, and the embedding cache used for clustering |
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| `REPRODUCIBILITY.md` | How to re-run the analysis from these files |
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## What is not included
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No evidence spans from the open codes, no tweet text, no generated report text (generations can repeat personal data from crisis
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posts), and no ReliefWeb documents (copyright of the publishing organisations). Use the
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manifests to retrieve the sources and verify them against the hashes.
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## Limitations
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The schema was induced from 56 Cyclone Idai reports, 44 of them OCHA's, so it chiefly reflects
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OCHA reporting practice. The human validation used one annotator on Idai only. Judge labels are
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LLM outputs. HumAID is a labelled sample of English-language tweets, not social media at large.
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## Licence
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CC BY-NC-SA 4.0, inherited from HumAID (Alam et al., 2021) for the tweet-ID manifest.
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## Citation
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```bibtex
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@misc{kumar2026sitrepgap,
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title = {Looking Complete Is Not Being Grounded: Evaluating {LLM} Sitreps Against Human-Authored Situation Reports},
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author = {Kumar, Sachin},
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year = {2026},
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eprint = {2610.18762},
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archivePrefix = {arXiv},
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primaryClass = {cs.CL},
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url = {https://arxiv.org/abs/2610.18762}
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}
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```
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