Triple
T1567937
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Very Large Telescope |
E33473
|
entity |
| Predicate | primaryMirrorDiameterPerUnit |
P2517
|
FINISHED |
| Object | 8.2 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: 8.2 meters | Statement: [Very Large Telescope, primaryMirrorDiameterPerUnit, 8.2 meters]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: primaryMirrorDiameterPerUnit Context triple: [Very Large Telescope, primaryMirrorDiameterPerUnit, 8.2 meters]
-
A.
primaryMirrorDiameter
chosen
Indicates the diameter of the primary mirror used in an optical system or instrument.
-
B.
twinTelescopeAperture
Indicates that two telescopes share the same aperture size or have apertures that are functionally equivalent.
-
C.
primaryMirrorShape
Indicates that one entity has a primary mirror whose geometric shape or curvature type is specified by the other entity.
-
D.
hasMeanRadius
Indicates that an entity possesses a specified average radius measurement, typically representing the mean distance from its center to its surface.
-
E.
angularSize
Indicates the apparent size of an object as seen from a given point, typically measured as the angle it subtends at the observer.
- 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_69a885f11b048190935025a035302715 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a90fccd4b48190a44012888a00af7f |
completed | March 5, 2026, 5:08 a.m. |
| PD | Predicate disambiguation | batch_69a907b872f0819096b3df6ad502c63e |
completed | March 5, 2026, 4:34 a.m. |
Created at: March 4, 2026, 7:27 p.m.