Triple
T25750487
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kepler |
E648457
|
entity |
| Predicate | focalPlaneSize |
P98265
|
FINISHED |
| Object | 95 megapixels |
—
|
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: 95 megapixels | Statement: [Kepler, focalPlaneSize, 95 megapixels]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: focalPlaneSize Context triple: [Kepler, focalPlaneSize, 95 megapixels]
-
A.
focalPlaneHeight
Indicates the vertical distance or elevation of the focal plane relative to a defined reference level or surface.
-
B.
hasFocalPlaneArea
chosen
Indicates that an entity has a specific area measurement associated with its focal plane.
-
C.
hasFocalPlane
Indicates that an optical system or imaging device possesses a specific focal plane where light is brought into focus.
-
D.
focalLength
Indicates the distance between a lens or mirror and its focal point, determining how strongly it converges or diverges light.
-
E.
flangeFocalDistance
Indicates the distance between a lens mount’s flange surface and the image sensor or film plane where the image comes into focus.
- 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_69e7ab314d788190b3abe19e114080e1 |
completed | April 21, 2026, 4:52 p.m. |
| NER | Named-entity recognition | batch_69f5fd7df2ac8190a206646c8640cec0 |
completed | May 2, 2026, 1:34 p.m. |
| PD | Predicate disambiguation | batch_69f4938262ac8190b41f922d0407d272 |
completed | May 1, 2026, 11:50 a.m. |
Created at: April 22, 2026, 4:34 a.m.