Triple
T18314878
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | NIRC2 camera |
E438729
|
entity |
| Predicate | narrowCameraPixelScale |
P37041
|
FINISHED |
| Object | approximately 0.01 arcseconds per pixel |
—
|
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 0.01 arcseconds per pixel | Statement: [NIRC2 camera, narrowCameraPixelScale, approximately 0.01 arcseconds per pixel]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: narrowCameraPixelScale Context triple: [NIRC2 camera, narrowCameraPixelScale, approximately 0.01 arcseconds per pixel]
-
A.
pixelScale
chosen
Indicates the ratio or conversion factor between pixel units and real-world or coordinate-space units in a representation or image.
-
B.
rearCameraAperture
Indicates the size or f-stop value of the aperture used by a device’s rear-facing camera when capturing images or video.
-
C.
focalLength
Indicates the distance between a lens or mirror and its focal point, determining how strongly it converges or diverges light.
-
D.
rearCameraSensorSize
Indicates the physical dimensions of the image sensor used by the device’s rear camera.
-
E.
viewfinderResolution
Indicates the resolution or level of detail provided by a device’s viewfinder display.
- 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_69d8b916a2d081909e249e4902f6aad9 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e5021cc70c8190bf43bd75e4af7381 |
completed | April 19, 2026, 4:26 p.m. |
| PD | Predicate disambiguation | batch_69e44fe4ee10819086b4142444fca1f5 |
completed | April 19, 2026, 3:45 a.m. |
Created at: April 10, 2026, 10:36 a.m.