datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
saas-vendor-outage-duration-incident-resolution-time-mttr
How long do SaaS vendor outages last? Incident resolution time per vendor, rebuilt daily
As of 2026-09-24 12:28 UTC. For every incident a vendor posted on its own public status
page with BOTH an opened time and a resolved time, this dataset computes
duration_minutes = resolved_at - started_at
and rolls it up per vendor. It is derived, every day, from the incident table in
saas-vendor-status-pages-outages-incidents-daily; the two are rebuilt by the same job and cannot
disagree.… See the full description on the dataset page: https://huggingface.co/datasets/APProjects/saas-vendor-outage-duration-incident-resolution-time-mttr.ofac-sdn-vessel-ownership-resolutionCanonical page: https://arcnautical.com/data/ofac-sdn-vessel-ownership-resolution/Permanent record (DOI): https://doi.org/10.5281/zenodo.22808695Publisher: ArcNautical. Public-source compilation (OFAC SDN + GLEIF), CC BY 4.0. This Hugging Face copy mirrors the canonical page; the Zenodo DOI is the citable identifier.
OFAC SDN vessel records (screened subset), snapshot 2026-09-16: flag and public GLEIF ownership-resolution stage
Public-record dataset of 1,527 screened… See the full description on the dataset page: https://huggingface.co/datasets/saltytar01/ofac-sdn-vessel-ownership-resolution.network-dns-resolution-coherence-risk-v0.1What this repo is for
Detect DNS instability before services fail.
Covers real operational signals:
rising resolution latency
SERVFAIL spikes
authoritative mismatch
cache poisoning
missing failover resolvers
Used by:
ISPs
cloud providers
enterprises
SRE teams
atc-conflict-detection-resolution-coherence-risk-v0.1What this repo is for
Detect when conflict resolution happens too late relative to detection.
Signals:
predicted time to conflict
resolution timing
separation margins
vectoring
altitude change
This predicts near-miss risk before separation loss.
instruction_conflict_resolution_v01Instruction Conflict Resolution v0.1
This evaluation dataset tests how models resolve conflicting instructions.
It targets a common failure mode: following the most recent or most forceful instruction even when it conflicts with higher-priority constraints.
This is not training data.
What it tests
Priority handling under instruction conflict
Refusal stability under escalation
Logical conflict handling for impossible constraints
Post-conflict integrity with no delayed leakage… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/instruction_conflict_resolution_v01.autonomous-driving-conflict-likelihood-and-resolution-window-v0.1What this dataset tests
Whether a system can predict conflict likelihood
based on intention divergence and social tension.
This is not collision prediction.
It is conflict risk prediction with an intervention window.
Required outputs
conflict_probability
time_to_conflict_s
resolution_window_s
safest_intervention_type
intervention_latency_budget_s
Scoring conventions
probabilities range 0 to 1
time values are seconds
intervention latency budget must be <= resolution window
Use… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/autonomous-driving-conflict-likelihood-and-resolution-window-v0.1.ABX-CS-002_pneumonia_resolution_lag-v0.1ABX-CS-002 Pneumonia Resolution Lag
Purpose
Detect early pneumonia non-improvement when clinical course stops matching the expected timeline under adequate therapy.
Core pattern
severity_index high
abx_exposure_index high
pneumonia_coherence_index drops
spo2_nonresponse_vs_expected stays high
rr_nonresponse_vs_expected stays high
later_icu_escalation_or_treatment_failure_flag appears
Files
data/train.csv
data/test.csv
scorer.py
Schema
Each row is one timepoint in a within series pneumonia… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/ABX-CS-002_pneumonia_resolution_lag-v0.1.customer-escalation-handling-and-resolution-quality-free
Customer Escalation Handling And Resolution Quality
Free sample for AI agent reliability dashboards, anomaly exploration, and observability-oriented analytics workflows.
What is included
conversation_traces.csv: 3256 rows, 10 columns
evaluation_sessions.csv: 1085 rows, 10 columns
judge_actions.csv: 2171 rows, 10 columns
quality_programs.csv: 27 rows, 10 columns
quality_scorecards.csv: 253 rows, 10 columns
review_outcomes.csv: 705 rows, 10 columns
Why this… See the full description on the dataset page: https://huggingface.co/datasets/Tekhnika/customer-escalation-handling-and-resolution-quality-free.