Triple
T2375132
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vera C. Rubin Observatory |
E46179
|
entity |
| Predicate | cameraAperture |
P31648
|
FINISHED |
| Object | 64 cm effective aperture |
—
|
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: 64 cm effective aperture | Statement: [Vera C. Rubin Observatory, cameraAperture, 64 cm effective aperture]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: cameraAperture Context triple: [Vera C. Rubin Observatory, cameraAperture, 64 cm effective aperture]
-
A.
hasAperture
Indicates that one entity possesses or is characterized by a specific opening, gap, or aperture.
-
B.
hasApertureClass
Indicates that one entity is classified according to a specific aperture category or class of another entity.
-
C.
objectiveLensDiameter
chosen
Indicates the diameter of the objective lens used in an optical device, such as a camera or telescope.
-
D.
auxiliaryTelescopeAperture
Indicates that one entity functions as the auxiliary telescope whose aperture (opening/diameter) is being specified or associated with another entity.
-
E.
telephotoOpticalZoom
Indicates that the relationship involves zooming in optically with a telephoto lens to magnify a subject without digital enlargement.
- 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_69a88a145268819083e2736cb835c696 |
completed | March 4, 2026, 7:37 p.m. |
| NER | Named-entity recognition | batch_69abca4d89248190be7d712d5fa8382b |
completed | March 7, 2026, 6:48 a.m. |
| PD | Predicate disambiguation | batch_69abc59d82f08190b7c36982d1ae783d |
completed | March 7, 2026, 6:28 a.m. |
Created at: March 4, 2026, 7:56 p.m.