Triple
T3068582
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ferrari World Abu Dhabi |
E62164
|
entity |
| Predicate | numberOfRides |
P42385
|
FINISHED |
| Object | more than 35 |
—
|
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 35 | Statement: [Ferrari World Abu Dhabi, numberOfRides, more than 35]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfRides Context triple: [Ferrari World Abu Dhabi, numberOfRides, more than 35]
-
A.
numberOfAttractions
chosen
Indicates the total count of attractions associated with a given entity or context.
-
B.
numberOfRollerCoasters
Indicates the quantity of roller coasters associated with a given entity.
-
C.
hasRideSystem
Indicates that one entity (typically an attraction or ride) uses or is associated with a particular ride system or ride mechanism.
-
D.
passesUsedForTransportation
Indicates that the passes are utilized as a means or instrument for transporting people or goods.
-
E.
numberOfRidersPerVehicle
Indicates the quantity of riders associated with each individual vehicle in the relationship.
- 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_69ad85793e5c8190a358049bc4a98d8c |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada0ffcc208190962cc9edcbf43c31 |
completed | March 8, 2026, 4:17 p.m. |
| PD | Predicate disambiguation | batch_69ad9624b7a0819091d255614f5819ea |
completed | March 8, 2026, 3:30 p.m. |
Created at: March 8, 2026, 3:02 p.m.