Triple
T12047566
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | iPhone 12 Pro |
E286823
|
entity |
| Predicate | supportsAppleProRAW |
P102942
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [iPhone 12 Pro, supportsAppleProRAW, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: supportsAppleProRAW Context triple: [iPhone 12 Pro, supportsAppleProRAW, true]
-
A.
supportsProResVideo
Indicates that one entity provides the capability for another entity to record, process, or handle video in the ProRes format.
-
B.
supportsProResDecode
Indicates that one entity is capable of decoding or otherwise handling ProRes-encoded media for another entity or in a given context.
-
C.
supportsProResEncode
Indicates that one entity provides the capability for another entity to perform ProRes video encoding.
-
D.
supportsProResLogEncoding
Indicates that one entity provides or enables ProRes Log encoding functionality for another entity or within a given context.
-
E.
supportsHDRFormat
Indicates that one entity is capable of handling, displaying, or processing content encoded in a specified High Dynamic Range (HDR) format for another entity.
- 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_69d6ab4780948190bdb9f7620c2ac27e |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d9100b4ca8819084845ca4c13e34ce |
completed | April 10, 2026, 2:58 p.m. |
| PD | Predicate disambiguation | batch_69d902bac9e08190aa1a99c835f29542 |
completed | April 10, 2026, 2:01 p.m. |
| PDg | Predicate description generation | batch_69d91006e14081909838412df082f794 |
completed | April 10, 2026, 2:58 p.m. |
Created at: April 8, 2026, 9:47 p.m.