Triple
T37479974
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Blackmagic Pocket Cinema Camera 4K |
E931387
|
entity |
| Predicate | supportsProResFlavor |
P41283
|
FINISHED |
| Object | ProRes Proxy |
E53639
|
NE 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: ProRes Proxy | Statement: [Blackmagic Pocket Cinema Camera 4K, supportsProResFlavor, ProRes Proxy]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: supportsProResFlavor Context triple: [Blackmagic Pocket Cinema Camera 4K, supportsProResFlavor, ProRes Proxy]
-
A.
supportsProResVideo
Indicates that one entity provides the capability for another entity to record, process, or handle video in the ProRes format.
-
B.
supportsProResEncode
chosen
Indicates that one entity provides the capability for another entity to perform ProRes video encoding.
-
C.
supportsProResEncodeDecode
Indicates that an entity provides the capability to both encode and decode media using the Apple ProRes format.
-
D.
supportsProResDecode
Indicates that one entity is capable of decoding or otherwise handling ProRes-encoded media for another entity or in a given context.
-
E.
supportsProResLogEncoding
Indicates that one entity provides or enables ProRes Log encoding functionality for another entity or within a given context.
- F. None of above.
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_6a037c8efcd4819088c2aeead65d93df |
completed | May 12, 2026, 7:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a408c4011b081909f979bdbbcb11b0a |
completed | June 28, 2026, 2:51 a.m. |
| PD | Predicate disambiguation | batch_6a037a13a1308190a202df66f4781855 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:17 p.m.