Triple
T11876775
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | HEP Five |
E282547
|
entity |
| Predicate | ferrisWheelHeightAboveGround |
P64476
|
FINISHED |
| Object | approximately 106 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 106 meters | Statement: [HEP Five, ferrisWheelHeightAboveGround, approximately 106 meters]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: ferrisWheelHeightAboveGround Context triple: [HEP Five, ferrisWheelHeightAboveGround, approximately 106 meters]
-
A.
heightAboveGround
chosen
Indicates the vertical distance of an entity measured from the ground surface directly beneath it.
-
B.
rideHeight
Indicates the vertical distance between a vehicle’s chassis and the ground, defining how high it sits relative to the surface.
-
C.
heightAboveSurroundings
Indicates that an entity’s vertical position or elevation is higher than that of its immediate surrounding area.
-
D.
revolvingRestaurantHeight
Indicates the height at which a revolving restaurant is situated, typically measured from ground level or sea level.
-
E.
aircraftHeight
Indicates the vertical distance or altitude of an aircraft relative to a reference level (such as ground or sea level).
- 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.