Triple
T26220667
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Serengeti Park Hodenhagen |
E655754
|
entity |
| Predicate | safetyRegulated |
P34837
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Serengeti Park Hodenhagen, safetyRegulated, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: safetyRegulated Context triple: [Serengeti Park Hodenhagen, safetyRegulated, true]
-
A.
hasSafetyRegulationCompliance
Indicates that an entity adheres to, satisfies, or is in conformity with specified safety regulations or standards.
-
B.
subjectToRegulation
chosen
Indicates that an entity is governed, constrained, or controlled by a specific rule, law, or regulatory framework.
-
C.
regulatedIn
Indicates that one entity’s activity, expression, or occurrence is controlled, influenced, or modulated by another entity within a specific context or system.
-
D.
safetyRequirement
Indicates that one entity specifies or imposes conditions, standards, or measures necessary to ensure the safety of another entity or activity.
-
E.
safetyRelevant
Indicates that the associated entity, condition, or information has a direct impact on safety or is critical for preventing harm or accidents.
- 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_69ee5b4a77e08190bfcb5f8ecdc55abd |
completed | April 26, 2026, 6:36 p.m. |
| NER | Named-entity recognition | batch_69f60d4f66748190819e060ab3dc492c |
completed | May 2, 2026, 2:42 p.m. |
| PD | Predicate disambiguation | batch_69f5f7fd90fc81909055b211368f9139 |
completed | May 2, 2026, 1:11 p.m. |
Created at: April 26, 2026, 8:56 p.m.