Triple
T321053
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Disney Skyliner |
E6415
|
entity |
| Predicate | hasCabins |
P12453
|
FINISHED |
| Object | enclosed gondola cabins |
—
|
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: enclosed gondola cabins | Statement: [Disney Skyliner, hasCabins, enclosed gondola cabins]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCabins Context triple: [Disney Skyliner, hasCabins, enclosed gondola cabins]
-
A.
hasCabinClass
Indicates that an entity (such as a booking, ticket, or seat) is associated with a specific cabin class (e.g., economy, business, first).
-
B.
cabinLocation
Indicates the spatial or geographic location associated with a cabin.
-
C.
hasCampground
Indicates that one entity provides, contains, or is associated with a campground facility or area for another entity.
-
D.
hasResortHotel
Indicates that one entity owns, includes, or is associated with a resort hotel as part of its facilities or offerings.
-
E.
hasCableCar
Indicates that one entity possesses, operates, or is served by a cable car system connecting it to other locations or points.
- 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_69a2e7933d6c8190bb2592ad13286ef2 |
completed | Feb. 28, 2026, 1:03 p.m. |
| NER | Named-entity recognition | batch_69a2ea8047c08190872c875e00f6e7dd |
completed | Feb. 28, 2026, 1:15 p.m. |
| PD | Predicate disambiguation | batch_69a2e946607081909c8b97473aaf8d1b |
completed | Feb. 28, 2026, 1:10 p.m. |
| PDg | Predicate description generation | batch_69a2ea7d03a88190aab72e61d8673488 |
completed | Feb. 28, 2026, 1:15 p.m. |
Created at: Feb. 28, 2026, 1:08 p.m.