Triple
T31150147
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nikon D6 |
E794049
|
entity |
| Predicate | meteringSystem |
P171196
|
FINISHED |
| Object | 180k-pixel RGB sensor |
—
|
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: 180k-pixel RGB sensor | Statement: [Nikon D6, meteringSystem, 180k-pixel RGB sensor]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: meteringSystem Context triple: [Nikon D6, meteringSystem, 180k-pixel RGB sensor]
-
A.
meteringSupport
Indicates that one entity provides or is compatible with metering capabilities (such as measurement, tracking, or billing of usage) for another entity.
-
B.
meterSystem
Indicates that one entity uses, is measured in, or is associated with a particular system of meters or measurement units.
-
C.
hasMeter
Indicates that one entity possesses, uses, or is associated with a specific meter (a measuring device or metrical pattern).
-
D.
meterForm
Indicates that one entity is the specific metrical pattern or verse form in which another entity (such as a poem or song) is composed.
-
E.
meter
Indicates a measurement relationship where one entity quantifies the length, distance, or extent of another in meters.
- 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_69f224d41bb48190a5621cd1485e3a30 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f69c6f01e881908fa84f5d429d37ae |
completed | May 3, 2026, 12:53 a.m. |
| PD | Predicate disambiguation | batch_69f69665cd9c819088c388fc82fec42e |
completed | May 3, 2026, 12:27 a.m. |
| PDg | Predicate description generation | batch_69f69c2127088190ae92c72461576d3b |
completed | May 3, 2026, 12:51 a.m. |
Created at: April 29, 2026, 9:06 p.m.