Triple
T657641
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sugar Bowl Resort |
E11682
|
entity |
| Predicate | hasTerrainPark |
P18015
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Sugar Bowl Resort, hasTerrainPark, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTerrainPark Context triple: [Sugar Bowl Resort, hasTerrainPark, yes]
-
A.
parkType
Indicates the specific category or classification of a park based on its designated use, management, or characteristics.
-
B.
hasSkiLifts
Indicates that one location or facility is equipped with ski lifts that provide transportation for skiers or visitors.
-
C.
hasCampground
Indicates that one entity provides, contains, or is associated with a campground facility or area for another entity.
-
D.
majorPark
Indicates that a park is classified as a major or primary park within a given area or system.
-
E.
hasScenicViewOf
Indicates that one entity offers a visually appealing or picturesque view of another entity.
- 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_69a4932862a0819098be659c814e4981 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a49fa55e048190bd9913c6c31772d0 |
completed | March 1, 2026, 8:20 p.m. |
| PD | Predicate disambiguation | batch_69a49d121cec81909986c91291bb4ca8 |
completed | March 1, 2026, 8:09 p.m. |
| PDg | Predicate description generation | batch_69a49ee356c0819085e2e82831cf1360 |
completed | March 1, 2026, 8:17 p.m. |
Created at: March 1, 2026, 7:36 p.m.