Triple
T30949531
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fujifilm X-S20 |
E788495
|
entity |
| Predicate | supportsProResRAWViaHDMI |
P207326
|
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: [Fujifilm X-S20, supportsProResRAWViaHDMI, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: supportsProResRAWViaHDMI Context triple: [Fujifilm X-S20, supportsProResRAWViaHDMI, true]
-
A.
supportsProResVideo
Indicates that one entity provides the capability for another entity to record, process, or handle video in the ProRes format.
-
B.
supportsProResEncodeDecode
Indicates that an entity provides the capability to both encode and decode media using the Apple ProRes format.
-
C.
supportsProResEncode
Indicates that one entity provides the capability for another entity to perform ProRes video encoding.
-
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.
supportsAppleProRAW
Indicates that one entity provides compatibility with or functionality for capturing, processing, or handling Apple ProRAW image 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_69f224c180f88190ad177372ee02b7e2 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_6a037c9141dc819098d7fcc36e69882c |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a0379e5174c8190a0bdde7e381b7624 |
completed | May 12, 2026, 7:05 p.m. |
| PDg | Predicate description generation | batch_6a037c7ee0388190a29faeb5cdb0950a |
completed | May 12, 2026, 7:16 p.m. |
Created at: April 29, 2026, 8:53 p.m.