Triple
T31256722
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fujifilm X-T20 |
E796993
|
entity |
| Predicate | exposureCompensation |
P171506
|
FINISHED |
| Object | dedicated dial |
—
|
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: dedicated dial | Statement: [Fujifilm X-T20, exposureCompensation, dedicated dial]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: exposureCompensation Context triple: [Fujifilm X-T20, exposureCompensation, dedicated dial]
-
A.
exposureCompensationRange
Indicates the range of exposure compensation values that can be applied to adjust image brightness relative to the camera’s metered exposure.
-
B.
exposureModes
Indicates the different ways or conditions under which an entity can be exposed to another entity, factor, or influence.
-
C.
exposureTime
Indicates the duration for which a subject or object is exposed to a particular condition, influence, or medium.
-
D.
exposureType
Indicates the specific manner or context in which one entity is exposed to another entity, condition, or influence.
-
E.
shutterSpeed
Indicates the exposure time setting of a camera, defining how long the shutter remains open during an image capture.
- F. None of above. chosen
Provenance (4 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_69f224dd5fdc81908a4cd24917b67668 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f69f80b62c8190bf2af2be0d3a7df8 |
completed | May 3, 2026, 1:06 a.m. |
| PD | Predicate disambiguation | batch_69f69d1bf8cc8190a78dfa5ab00daf3a |
completed | May 3, 2026, 12:55 a.m. |
| PDg | Predicate description generation | batch_69f69edae2448190925ce701c8792c52 |
completed | May 3, 2026, 1:03 a.m. |
Created at: April 29, 2026, 9:12 p.m.