Triple
T11876774
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | HEP Five |
E282547
|
entity |
| Predicate | ferrisWheelDiameter |
P44248
|
FINISHED |
| Object | approximately 75 meters |
—
|
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: approximately 75 meters | Statement: [HEP Five, ferrisWheelDiameter, approximately 75 meters]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: ferrisWheelDiameter Context triple: [HEP Five, ferrisWheelDiameter, approximately 75 meters]
-
A.
rideHeight
Indicates the vertical distance between a vehicle’s chassis and the ground, defining how high it sits relative to the surface.
-
B.
rotorDiameter
Indicates the relationship where a rotor is associated with a specific measurement representing the diameter of its circular span.
-
C.
fanDiameter
Indicates the size of a fan measured as the length of a straight line passing through its center from one edge to the opposite edge.
-
D.
wheelDiameter
chosen
Indicates the size of a wheel measured across its diameter.
-
E.
driverDiameter
Indicates the size of the circular cross-section of a driver component, typically measured as the distance across its widest point.
- 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_69d6ab2945d081908a5851c916cbcfb5 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d8d39d2934819093b9f7006f45e5cb |
completed | April 10, 2026, 10:40 a.m. |
| PD | Predicate disambiguation | batch_69d8bb272f88819090c37c944c5a60ab |
completed | April 10, 2026, 8:56 a.m. |
Created at: April 8, 2026, 9:44 p.m.