Triple
T38619581
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Blackmagic URSA Broadcast G2 |
E936831
|
entity |
| Predicate | hasGammaCurve |
P171705
|
FINISHED |
| Object | Blackmagic Film |
—
|
NE NERFINISHED |
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: Blackmagic Film | Statement: [Blackmagic URSA Broadcast G2, hasGammaCurve, Blackmagic Film]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasGammaCurve Context triple: [Blackmagic URSA Broadcast G2, hasGammaCurve, Blackmagic Film]
-
A.
gammaCurveType
chosen
Indicates the specific type or model of gamma correction curve applied in a color or image processing context.
-
B.
assumedDisplayGamma
Indicates that a specific gamma value is presumed to characterize the display’s tone response or brightness mapping behavior.
-
C.
hasWiderGamutThan
Indicates that one entity supports or encompasses a broader range or spectrum (e.g., of colors or values) than another entity.
-
D.
hasAlphaEnhancement
Indicates that an entity possesses an increased or augmented alpha-related property, characteristic, or capability compared to a baseline.
-
E.
supportsColorSampling
Indicates that one entity can perform or accommodate color sampling operations on another entity or its data.
- 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_69f76ed403208190b862dc795171353f |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fcf825ca7081909d06b0df33eb33f9 |
completed | May 7, 2026, 8:37 p.m. |
| PD | Predicate disambiguation | batch_69fcf42160f0819096812a8bf590875e |
completed | May 7, 2026, 8:20 p.m. |
Created at: May 3, 2026, 4:32 p.m.