Triple
T29961
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Heavenly Mountain Resort |
E598
|
entity |
| Predicate | hasLiftType |
P1984
|
FINISHED |
| Object | gondola |
—
|
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: gondola | Statement: [Heavenly Mountain Resort, hasLiftType, gondola]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLiftType Context triple: [Heavenly Mountain Resort, hasLiftType, gondola]
-
A.
hasElevators
Indicates that one entity is equipped with or contains one or more elevators for vertical transportation.
-
B.
aircraftType
Indicates the specific model or category of aircraft associated with an entity or event.
-
C.
hasGroundTransportation
Indicates that an entity provides, includes, or is connected to transportation services or options that operate on land (e.g., cars, buses, trains).
-
D.
hasEscalators
Indicates that one entity is equipped with or contains escalators that can be used for movement between different levels or areas.
-
E.
hasMaterialType
Indicates that something is composed of, made from, or characterized by a specific type of material.
- 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_69a2479dec388190967ba648663442c9 |
completed | Feb. 28, 2026, 1:40 a.m. |
| NER | Named-entity recognition | batch_69a2490019948190a89bb0910c60d462 |
completed | Feb. 28, 2026, 1:46 a.m. |
| PD | Predicate disambiguation | batch_69a2486d40348190b2d21fc444f499a6 |
completed | Feb. 28, 2026, 1:44 a.m. |
| PDg | Predicate description generation | batch_69a248fef2b881908180bd4e32e58cb5 |
completed | Feb. 28, 2026, 1:46 a.m. |
Created at: Feb. 28, 2026, 1:44 a.m.