Triple
T34394832
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | First Class (Singapore Airlines cabin) |
E882800
|
entity |
| Predicate | entertainmentBrand |
P1500
|
FINISHED |
| Object | KrisWorld |
—
|
NE NERFINISHED |
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: KrisWorld | Statement: [First Class (Singapore Airlines cabin), entertainmentBrand, KrisWorld]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: entertainmentBrand Context triple: [First Class (Singapore Airlines cabin), entertainmentBrand, KrisWorld]
-
A.
hasEntertainmentBrand
Indicates that one entity owns, operates, or is formally associated with an entertainment-related brand or franchise.
-
B.
mediaBrandOf
Indicates that a media outlet, channel, or publication is the brand associated with or responsible for a given piece of media content or product.
-
C.
notableBrandElement
Indicates that one entity is a significant or distinguishing brand-related feature, component, or asset of another entity.
-
D.
brand
chosen
Indicates that one entity is the commercial brand or label under which another entity (such as a product, service, or organization) is marketed or identified.
-
E.
popularBrand
Indicates that a brand is widely liked, recognized, or frequently chosen by many people.
- 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_69f349c1304081909331872829e38106 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69f7805ce6208190ac6dbd9c97989978 |
completed | May 3, 2026, 5:05 p.m. |
| PD | Predicate disambiguation | batch_69f77956ec648190ba4fb7e9d83fd107 |
completed | May 3, 2026, 4:35 p.m. |
Created at: May 1, 2026, 1:59 a.m.