Triple
T14746972
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SkyCoaster |
E346497
|
entity |
| Predicate | hasTypicalHeightRange |
P573
|
FINISHED |
| Object | 30–91 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: 30–91 meters | Statement: [SkyCoaster, hasTypicalHeightRange, 30–91 meters]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTypicalHeightRange Context triple: [SkyCoaster, hasTypicalHeightRange, 30–91 meters]
-
A.
typicalHeight
chosen
Indicates the usual or characteristic height associated with an entity, such as a person, object, or species.
-
B.
shoulderHeightRange
Indicates the range of vertical height measured from the ground to an entity’s shoulders.
-
C.
estimatedHeadHeightInMeters
Indicates the estimated vertical height of a person's head, measured in meters.
-
D.
heightDescription
Indicates how tall an entity is, typically expressed in descriptive or qualitative terms rather than a precise measurement.
-
E.
averageHeight
Indicates that the relationship specifies the mean height value calculated from a set of entities or measurements.
- 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_69d822e6f1c88190bc494d491a907114 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69dec7d116e88190828b163b18d80f68 |
completed | April 14, 2026, 11:03 p.m. |
| PD | Predicate disambiguation | batch_69de8bf9331481909582045cd567d91f |
completed | April 14, 2026, 6:48 p.m. |
Created at: April 10, 2026, 1:30 a.m.