Triple
T37479993
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Blackmagic Pocket Cinema Camera 4K |
E931387
|
entity |
| Predicate | dualNativeISOValues |
P188379
|
FINISHED |
| Object | ISO 400 |
—
|
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: ISO 400 | Statement: [Blackmagic Pocket Cinema Camera 4K, dualNativeISOValues, ISO 400]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: dualNativeISOValues Context triple: [Blackmagic Pocket Cinema Camera 4K, dualNativeISOValues, ISO 400]
-
A.
nativeISO
Indicates that an entity inherently uses or supports a specified ISO standard or ISO-based format without requiring conversion or adaptation.
-
B.
nativeISOmax
Indicates the maximum native ISO sensitivity a camera sensor can achieve without using extended or boosted ISO modes.
-
C.
nativeISOmin
Indicates that the subject entity has a minimum native ISO sensitivity value equal to the specified object value.
-
D.
hasDualSpace
Indicates that one mathematical space is the dual space consisting of all linear functionals defined on another space.
-
E.
hasDualBasis
Indicates that one mathematical structure serves as the dual basis corresponding to another basis, typically in a dual vector space.
- 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_69f76ec382248190b47844df596123c6 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fba68077788190b311e027435fcf87 |
completed | May 6, 2026, 8:37 p.m. |
| PD | Predicate disambiguation | batch_69fba34c65ac8190b298f0f00d1dcc0e |
completed | May 6, 2026, 8:23 p.m. |
| PDg | Predicate description generation | batch_69fba67f78348190ab160988e4698394 |
completed | May 6, 2026, 8:37 p.m. |
Created at: May 3, 2026, 4:17 p.m.