Triple
T1993368
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mount Bachelor |
E43300
|
entity |
| Predicate | skiAreaVerticalDrop |
P34387
|
FINISHED |
| Object | 3365 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: 3365 feet | Statement: [Mount Bachelor, skiAreaVerticalDrop, 3365 feet]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: skiAreaVerticalDrop Context triple: [Mount Bachelor, skiAreaVerticalDrop, 3365 feet]
-
A.
skiVerticalDrop
chosen
Indicates the vertical distance in elevation from the top to the bottom of a ski run or ski area.
-
B.
totalAscent
Indicates the total cumulative elevation gained over the course of a movement, route, or activity.
-
C.
hasSkiLifts
Indicates that one location or facility is equipped with ski lifts that provide transportation for skiers or visitors.
-
D.
alpineSkiingVenue
Indicates that one entity serves as a venue or location where alpine skiing activities or events take place in relation to another entity.
-
E.
mountainType
Indicates the specific classification or category of a mountain based on its geological or physical characteristics.
- 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_69a88714cf2c819081644be450b8356e |
completed | March 4, 2026, 7:25 p.m. |
| NER | Named-entity recognition | batch_69abb8ee02dc81908fec9fd8df7a4f40 |
completed | March 7, 2026, 5:34 a.m. |
| PD | Predicate disambiguation | batch_69abb79ad6888190be99943a9c73cf3e |
completed | March 7, 2026, 5:28 a.m. |
Created at: March 4, 2026, 7:37 p.m.