Triple
T8415057
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Apple A11 Bionic |
E198711
|
entity |
| Predicate | supports4KFrameRate |
P41984
|
FINISHED |
| Object | 60 fps |
—
|
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: 60 fps | Statement: [Apple A11 Bionic, supports4KFrameRate, 60 fps]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: supports4KFrameRate Context triple: [Apple A11 Bionic, supports4KFrameRate, 60 fps]
-
A.
supports4KVideoRecording
chosen
Indicates that the subject is capable of recording video at 4K (Ultra HD) resolution.
-
B.
propertyType_maxFramerate
Indicates the maximum frame rate value that the property can support or is configured to allow.
-
C.
supportsProResDecode
Indicates that one entity is capable of decoding or otherwise handling ProRes-encoded media for another entity or in a given context.
-
D.
supportsDisplayResolution
Indicates that one entity is capable of operating with, rendering, or otherwise accommodating the specified display resolution of another entity.
-
E.
supportsProResEncode
Indicates that one entity provides the capability for another entity to perform ProRes video encoding.
- 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_69ca831201b481909e137936ef99ff11 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cb83e443a08190983d9a0a61e0f781 |
completed | March 31, 2026, 8:20 a.m. |
| PD | Predicate disambiguation | batch_69cb70d70ea081909c3dc1bd2ec14f85 |
completed | March 31, 2026, 6:59 a.m. |
Created at: March 30, 2026, 6:06 p.m.