Triple
T30358411
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | X-Trans CMOS |
E772206
|
entity |
| Predicate | sensorFormatCropFactor |
P169098
|
FINISHED |
| Object | 1.5x |
—
|
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: 1.5x | Statement: [X-Trans CMOS, sensorFormatCropFactor, 1.5x]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sensorFormatCropFactor Context triple: [X-Trans CMOS, sensorFormatCropFactor, 1.5x]
-
A.
cropFactor
chosen
Indicates the ratio between a camera sensor’s dimensions and a reference format (typically 35mm/full-frame), expressing how much the field of view is effectively “cropped” compared to that standard.
-
B.
sensorFormat
Indicates the data encoding or representation standard used by a sensor to output its measurements.
-
C.
rearCameraSensorSize
Indicates the physical dimensions of the image sensor used by the device’s rear camera.
-
D.
viewfinderResolution
Indicates the resolution or level of detail provided by a device’s viewfinder display.
-
E.
focalLength
Indicates the distance between a lens or mirror and its focal point, determining how strongly it converges or diverges light.
- 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_69f2248c6f5c8190a6177842bf791a3c |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f682417ec08190982dd9acf7219742 |
completed | May 2, 2026, 11:01 p.m. |
| PD | Predicate disambiguation | batch_69f67e40af9881908de3a4aa15f70a83 |
completed | May 2, 2026, 10:44 p.m. |
Created at: April 29, 2026, 7:57 p.m.