Triple
T30358265
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nikon F-mount DSLR system |
E772203
|
entity |
| Predicate | meteringSupport |
P169096
|
FINISHED |
| Object | CPU lenses |
—
|
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: CPU lenses | Statement: [Nikon F-mount DSLR system, meteringSupport, CPU lenses]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: meteringSupport Context triple: [Nikon F-mount DSLR system, meteringSupport, CPU lenses]
-
A.
hasMeter
Indicates that one entity possesses, uses, or is associated with a specific meter (a measuring device or metrical pattern).
-
B.
measurementSetting
Indicates the specific conditions, parameters, or configuration under which a measurement is taken or recorded.
-
C.
hasMeasurement
Indicates that an entity is associated with a specific measured value, often including a unit or measurement context.
-
D.
supportsUserDefinedMeasurements
Indicates that an entity allows users to create, configure, and use their own custom measurement definitions or metrics.
-
E.
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.
- 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_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. |
| PDg | Predicate description generation | batch_69f679496c188190ba585792f987a1f4 |
completed | May 2, 2026, 10:23 p.m. |
Created at: April 29, 2026, 7:57 p.m.