Triple
T30358240
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nikon F-mount DSLR system |
E772203
|
entity |
| Predicate | sensorFormats |
P85623
|
FINISHED |
| Object | DX format |
—
|
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: DX format | Statement: [Nikon F-mount DSLR system, sensorFormats, DX format]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sensorFormats Context triple: [Nikon F-mount DSLR system, sensorFormats, DX format]
-
A.
sensorFormat
chosen
Indicates the data encoding or representation standard used by a sensor to output its measurements.
-
B.
detectorFormat
Indicates the specific data or signal representation used by a detector to encode or output its measurements.
-
C.
typicalPictureFormat
Indicates the standard or most commonly used picture format associated with an entity (such as a device, medium, or context).
-
D.
featuresFormat
Indicates that something (such as a product, service, or medium) is presented, delivered, or made available in a particular format or configuration.
-
E.
scanFormat
Indicates the format or pattern used when scanning or parsing input data.
- 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_69f678d019fc8190913662cd2f87b857 |
completed | May 2, 2026, 10:21 p.m. |
Created at: April 29, 2026, 7:57 p.m.