Triple
T2603476
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hillsborough disaster |
E58597
|
entity |
| Predicate | impactOnPolicing |
P35323
|
FINISHED |
| Object | scrutiny of South Yorkshire Police practices |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
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.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: scrutiny of South Yorkshire Police practices | Statement: [Hillsborough disaster, impactOnPolicing, scrutiny of South Yorkshire Police practices]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: impactOnPolicing Context triple: [Hillsborough disaster, impactOnPolicing, scrutiny of South Yorkshire Police practices]
-
A.
impactOnLawEnforcement
chosen
Indicates the effect or consequences that something has on law enforcement activities, operations, or effectiveness.
-
B.
policingModel
Indicates the approach, strategy, or framework used to organize and conduct policing activities or law enforcement operations.
-
C.
lawEnforcementLevel
Indicates the degree or intensity of law enforcement presence, activity, or strictness applied in a given context.
-
D.
socialImpact
Indicates the extent to which an action, entity, or relationship affects society or communities, whether positively or negatively.
-
E.
lawEnforcementResponse
Indicates the actions or measures taken by law enforcement agencies in reaction to an incident, behavior, or situation.
- F. None of above.
Provenance (3 batches)
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_69ab4ac3523881909679750c9f8c2dec |
completed | March 6, 2026, 9:44 p.m. |
| NER | Named-entity recognition | batch_69abd48241c48190bc80418212e33bc8 |
completed | March 7, 2026, 7:32 a.m. |
| PD | Predicate disambiguation | batch_69abd0d4e8648190b612eb09aa085451 |
completed | March 7, 2026, 7:16 a.m. |
Created at: March 6, 2026, 9:49 p.m.