Triple
T2298265
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Air New Zealand |
E51667
|
entity |
| Predicate | safetyVideoStyle |
P39059
|
FINISHED |
| Object | humorous |
—
|
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: humorous | Statement: [Air New Zealand, safetyVideoStyle, humorous]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: safetyVideoStyle Context triple: [Air New Zealand, safetyVideoStyle, humorous]
-
A.
musicVideoStyle
Indicates the stylistic or aesthetic approach used in the creation or presentation of a music video.
-
B.
safety
Indicates that an entity provides, ensures, or is associated with protection from harm, danger, or risk for another entity or within a given context.
-
C.
safetyRelevant
Indicates that the associated entity, condition, or information has a direct impact on safety or is critical for preventing harm or accidents.
-
D.
safetyPositioning
Indicates the spatial or situational arrangement of entities to ensure or enhance safety.
-
E.
notableSafety
Indicates that an entity is recognized for having significant safety characteristics, performance, or impact relative to others.
- 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_69a88b0a9f248190bcff941463d8f65a |
completed | March 4, 2026, 7:42 p.m. |
| NER | Named-entity recognition | batch_69abcd0e42248190ada33b84d75caa64 |
completed | March 7, 2026, 7 a.m. |
| PD | Predicate disambiguation | batch_69abc589295c819092989820c2b4e9d8 |
completed | March 7, 2026, 6:28 a.m. |
| PDg | Predicate description generation | batch_69abcd0d01ac8190935fe904905cb233 |
completed | March 7, 2026, 7 a.m. |
Created at: March 4, 2026, 7:49 p.m.