Triple
T15016959
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Faraya–Mzaar ski area |
E377980
|
entity |
| Predicate | hasApproximateNumberOfLifts |
P116401
|
FINISHED |
| Object | more than 15 lifts |
—
|
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: more than 15 lifts | Statement: [Faraya–Mzaar ski area, hasApproximateNumberOfLifts, more than 15 lifts]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasApproximateNumberOfLifts Context triple: [Faraya–Mzaar ski area, hasApproximateNumberOfLifts, more than 15 lifts]
-
A.
hasLift
Indicates that one entity is equipped with, contains, or provides access to a lift (elevator).
-
B.
hasNumberOfElevatorBanks
Indicates the relationship specifying how many distinct elevator banks are present in or associated with a given entity.
-
C.
hasLiftType
Indicates the specific type or category of lift associated with an entity.
-
D.
liftHillCount
Indicates the number of lift hills present in or associated with an entity (such as a ride or track).
-
E.
numberOfElevators
Indicates the total count of elevators associated with a given entity or location.
- 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_69d85cd3a3c881908c71fc424d459c17 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded7633fcc8190b2231f43252bc46f |
completed | April 15, 2026, 12:10 a.m. |
| PD | Predicate disambiguation | batch_69de9a67cbc481909c19c2de57de4eb7 |
completed | April 14, 2026, 7:50 p.m. |
| PDg | Predicate description generation | batch_69deb1a88d588190996afa8e5b32b552 |
completed | April 14, 2026, 9:29 p.m. |
Created at: April 10, 2026, 2:55 a.m.