Triple
T33320041
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | United Polaris |
E853111
|
entity |
| Predicate | diningConcept |
P9631
|
FINISHED |
| Object | restaurant-style service on many flights |
—
|
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: restaurant-style service on many flights | Statement: [United Polaris, diningConcept, restaurant-style service on many flights]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: diningConcept Context triple: [United Polaris, diningConcept, restaurant-style service on many flights]
-
A.
diningStyle
chosen
Indicates the manner or format in which dining is conducted, such as casual, formal, buffet, or family-style.
-
B.
isDiningDestination
Indicates that a place serves as a destination where people go specifically to eat meals or dine.
-
C.
hasDiningFeature
Indicates that something possesses a specific characteristic, amenity, or attribute related to dining.
-
D.
alsoEats
Indicates that an entity consumes something in addition to another item or items it already eats.
-
E.
hasCharacterDining
Indicates that an entity offers or includes dining experiences where guests can eat while interacting with costumed characters.
- 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_69f349685f088190b8fda44083a018a9 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f6e3156ea48190b604e414665ef351 |
completed | May 3, 2026, 5:54 a.m. |
| PD | Predicate disambiguation | batch_69f6de0b9ba48190887c9eb5d06a2e94 |
completed | May 3, 2026, 5:32 a.m. |
Created at: May 1, 2026, 1:33 a.m.