Triple
T16336497
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | PRISM |
E396690
|
entity |
| Predicate | imageAcquisitionMode |
P100170
|
FINISHED |
| Object | stereo mode |
—
|
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: stereo mode | Statement: [PRISM, imageAcquisitionMode, stereo mode]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: imageAcquisitionMode Context triple: [PRISM, imageAcquisitionMode, stereo mode]
-
A.
acquisitionMode
chosen
Indicates the method or process by which one entity obtains, receives, or gains another entity or resource.
-
B.
exposureModes
Indicates the different ways or conditions under which an entity can be exposed to another entity, factor, or influence.
-
C.
acquisitionPattern
Indicates the characteristic way in which one entity acquires or obtains another entity or resource, such as the method, frequency, or structure of the acquisition.
-
D.
cameraConfiguration
Indicates the specific setup or arrangement of a camera’s parameters or components in a given context.
-
E.
cameraStyle
Indicates the characteristic visual approach or technique used by a camera in capturing or presenting imagery.
- 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_69d87f26864c819088365ca381a003c2 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e2c4e3af7881908a3116c41ed69115 |
completed | April 17, 2026, 11:40 p.m. |
| PD | Predicate disambiguation | batch_69e226eba9b48190af6e80d3d1c2aed3 |
completed | April 17, 2026, 12:26 p.m. |
Created at: April 10, 2026, 5:07 a.m.