Triple
T22343506
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hate Crime Statistics annual report |
E552332
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | law enforcement data publication |
C35410
|
CONCEPT FINISHED |
How this triple was built (1 step)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
CD
Concept disambiguation
gpt-5-mini-2025-08-07
Target class: law enforcement data publication Context triple: [Hate Crime Statistics annual report, instanceOf, law enforcement data publication]
-
A.
law enforcement data
Law enforcement data is information collected, generated, or used by policing and criminal justice agencies about incidents, individuals, activities, and operations for the purposes of investigation, public safety, and legal compliance.
-
B.
criminal justice statistics publication
chosen
A criminal justice statistics publication is an official report that compiles, analyzes, and presents quantitative data on crime, law enforcement, courts, and corrections to inform policy, research, and public understanding.
-
C.
crime data program
A crime data program is a software system that collects, stores, analyzes, and visualizes crime-related information to support law enforcement, policy-making, and public safety decision-making.
-
D.
policy-relevant data compendium
A policy-relevant data compendium is a curated, structured collection of datasets and indicators organized to inform, support, and evaluate public policy decisions on specific issues or sectors.
-
E.
crime data collection program
A crime data collection program is a software system that systematically gathers, validates, and stores crime-related information from various sources to support analysis, reporting, and decision-making.
- F. None of above.
Provenance (1 batch)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69e11e494eec81909c4d2d51f69499d9 |
completed | April 16, 2026, 5:37 p.m. |
Created at: April 16, 2026, 8:43 p.m.