Triple
T22920083
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Arthur – The Ride |
E568835
|
entity |
| Predicate | hasRideVehicles |
P60619
|
FINISHED |
| Object | inverted suspended trains |
—
|
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: inverted suspended trains | Statement: [Arthur – The Ride, hasRideVehicles, inverted suspended trains]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRideVehicles Context triple: [Arthur – The Ride, hasRideVehicles, inverted suspended trains]
-
A.
hasVehicle
Indicates that one entity possesses, owns, or is assigned a vehicle.
-
B.
hasVehicleCollection
chosen
Indicates that an entity possesses or maintains a set or collection of vehicles.
-
C.
vehicleFor
Indicates that one entity serves as the means of transportation or conveyance for another entity.
-
D.
hasRidingAssociation
Indicates an association where one entity is related to another through the act or context of riding (e.g., serving as rider, mount, or riding partner).
-
E.
hasVehicularUse
Indicates that something is used for, intended for, or associated with operation by vehicles or vehicular traffic.
- 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_69e2458d90c88190a58cead4e781ca6a |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f180d40f98819096210c097b47d43b |
completed | April 29, 2026, 3:53 a.m. |
| PD | Predicate disambiguation | batch_69ef3b7c5fc081909ac50c5c8569cc19 |
completed | April 27, 2026, 10:33 a.m. |
Created at: April 17, 2026, 3:42 p.m.