Triple
T5870478
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hillsborough Stadium |
E130502
|
entity |
| Predicate | safetyRegulationChange |
P67636
|
FINISHED |
| Object | contributed to Taylor Report |
—
|
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: contributed to Taylor Report | Statement: [Hillsborough Stadium, safetyRegulationChange, contributed to Taylor Report]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: safetyRegulationChange Context triple: [Hillsborough Stadium, safetyRegulationChange, contributed to Taylor Report]
-
A.
safetyRegulationEffect
Indicates how a safety regulation influences or changes the conditions, behaviors, or outcomes associated with the regulated entities.
-
B.
safetyRegulationsUpdatedAfter
Indicates that one set of safety regulations was revised or brought into effect at a later time than another set of safety regulations.
-
C.
safetyChangesImplemented
Indicates that specific safety-related modifications or measures have been put into effect.
-
D.
regulationImpact
Indicates how a regulation influences, constrains, or alters the behavior, performance, or outcomes associated with the related entities.
-
E.
regulationAtIssue
Indicates that a specific regulation is the subject of concern, dispute, or analysis in the given context.
- F. None of above. chosen
Provenance (4 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_69c0085047dc8190af24e311edad3c07 |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c044ffaef081909faaa7f420a3b9b7 |
completed | March 22, 2026, 7:37 p.m. |
| PD | Predicate disambiguation | batch_69c03347e51c81909053bcf34e3b88ab |
completed | March 22, 2026, 6:22 p.m. |
| PDg | Predicate description generation | batch_69c044fe17d08190b9bf47b13863ef52 |
completed | March 22, 2026, 7:37 p.m. |
Created at: March 22, 2026, 3:56 p.m.