Triple
T18314880
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | NIRC2 camera |
E438729
|
entity |
| Predicate | fieldOfViewMode |
P2524
|
FINISHED |
| Object | narrow field of view |
—
|
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: narrow field of view | Statement: [NIRC2 camera, fieldOfViewMode, narrow field of view]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fieldOfViewMode Context triple: [NIRC2 camera, fieldOfViewMode, narrow field of view]
-
A.
hasFieldOfView
chosen
Indicates that one entity possesses a visual coverage area within which it can perceive or detect other entities or regions.
-
B.
viewfinderType
Indicates the type or kind of viewfinder associated with or used by an entity.
-
C.
hasViewingAngles
Indicates that one entity possesses or is characterized by specific viewing angles relative to another entity or reference frame.
-
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_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.