Triple
T28376958
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Grizzly Peak Airfield |
E718778
|
entity |
| Predicate | containsDining |
P55802
|
FINISHED |
| Object | Smokejumpers Grill |
—
|
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: Smokejumpers Grill | Statement: [Grizzly Peak Airfield, containsDining, Smokejumpers Grill]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: containsDining Context triple: [Grizzly Peak Airfield, containsDining, Smokejumpers Grill]
-
A.
hasDiningComponent
Indicates that something includes or is associated with a dining-related part, feature, or function.
-
B.
hasDiningFeature
chosen
Indicates that something possesses a specific characteristic, amenity, or attribute related to dining.
-
C.
hasDiningOptionType
Indicates that an entity offers or is associated with a specific type or category of dining option (e.g., dine-in, takeout, delivery).
-
D.
hasCharacterDining
Indicates that an entity offers or includes dining experiences where guests can eat while interacting with costumed characters.
-
E.
hasDiningFocus
Indicates that an entity is primarily oriented toward or specialized in dining-related activities, services, or experiences.
- 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_69eff6ee5afc8190bd7375a29f0cc6c6 |
completed | April 27, 2026, 11:53 p.m. |
| NER | Named-entity recognition | batch_69fd7b0503a08190ba07338365b6fcc9 |
completed | May 8, 2026, 5:56 a.m. |
| PD | Predicate disambiguation | batch_69fd7a9733dc81909199f453c0cc2bc1 |
completed | May 8, 2026, 5:54 a.m. |
Created at: April 28, 2026, 1:03 a.m.