Triple
T9733744
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pirates of the Caribbean (Disneyland Paris Adventureland version) |
E236006
|
entity |
| Predicate | hasRideVehicle |
P7735
|
FINISHED |
| Object | multi-row boats |
—
|
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: multi-row boats | Statement: [Pirates of the Caribbean (Disneyland Paris Adventureland version), hasRideVehicle, multi-row boats]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRideVehicle Context triple: [Pirates of the Caribbean (Disneyland Paris Adventureland version), hasRideVehicle, multi-row boats]
-
A.
hasVehicle
chosen
Indicates that one entity possesses, owns, or is assigned a vehicle.
-
B.
hasRideCycle
Indicates that one entity is associated with, or participates in, a recurring sequence or cycle of rides or ride operations.
-
C.
vehicleUsed
Indicates that a particular vehicle is utilized or employed in performing an action, event, or activity.
-
D.
hasVehicleAccess
Indicates that an entity is permitted to use or enter a particular vehicle.
-
E.
mainVehicle
Indicates that one vehicle is the primary or most important vehicle associated with a given entity or context.
- 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_69ca84d313e88190983ee6ffd0ef60d2 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cd9eb54fe481908b0202f104b75dc1 |
completed | April 1, 2026, 10:39 p.m. |
| PD | Predicate disambiguation | batch_69cd03c6ffc88190a5e9569e19122ad5 |
completed | April 1, 2026, 11:38 a.m. |
Created at: March 30, 2026, 8:22 p.m.