Triple
T1957456
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Whiteface Mountain |
E42301
|
entity |
| Predicate | skiVerticalDrop |
P34387
|
FINISHED |
| Object | 3430 feet |
—
|
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: 3430 feet | Statement: [Whiteface Mountain, skiVerticalDrop, 3430 feet]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: skiVerticalDrop Context triple: [Whiteface Mountain, skiVerticalDrop, 3430 feet]
-
A.
totalAscent
Indicates the total cumulative elevation gained over the course of a movement, route, or activity.
-
B.
numberOfRollerCoasters
Indicates the quantity of roller coasters associated with a given entity.
-
C.
hasSkiLifts
Indicates that one location or facility is equipped with ski lifts that provide transportation for skiers or visitors.
-
D.
numberOfWaterRides
Indicates the quantity of water-based rides associated with a given entity.
-
E.
hasTerrainPark
Indicates that a location or facility includes a designated terrain park area for activities such as skiing or snowboarding.
- 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_69a8870eea088190a38781990812a9bc |
completed | March 4, 2026, 7:25 p.m. |
| NER | Named-entity recognition | batch_69abb68a8e608190bc37a85913b3cd44 |
completed | March 7, 2026, 5:24 a.m. |
| PD | Predicate disambiguation | batch_69abaff5dbd48190a9d36ca60de151db |
completed | March 7, 2026, 4:56 a.m. |
| PDg | Predicate description generation | batch_69abb6893eb881908923f0168374596a |
completed | March 7, 2026, 5:24 a.m. |
Created at: March 4, 2026, 7:36 p.m.