Triple
T4565241
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Taniwha Tubes |
E121892
|
entity |
| Predicate | safetyProvidedBy |
P12725
|
FINISHED |
| Object | lifeguards |
—
|
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: lifeguards | Statement: [Taniwha Tubes, safetyProvidedBy, lifeguards]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: safetyProvidedBy Context triple: [Taniwha Tubes, safetyProvidedBy, lifeguards]
-
A.
safetyProfile
Indicates the overall level and characteristics of risk or harm associated with something, typically summarizing how safe it is under specified conditions.
-
B.
safetyCategory
Indicates the classification of something according to its level or type of safety.
-
C.
safety
chosen
Indicates that an entity provides, ensures, or is associated with protection from harm, danger, or risk for another entity or within a given context.
-
D.
safetyRelevant
Indicates that the associated entity, condition, or information has a direct impact on safety or is critical for preventing harm or accidents.
-
E.
hasSafetyCertificate
Indicates that an entity possesses or has been granted a valid safety certificate.
- 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_69bd463f156881908a99aca69c5721ac |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd589cde9081909b84186d700fc463 |
completed | March 20, 2026, 2:24 p.m. |
| PD | Predicate disambiguation | batch_69bd52254c648190a5144cfe8fa7e409 |
completed | March 20, 2026, 1:56 p.m. |
Created at: March 20, 2026, 1:09 p.m.