Triple
T30481866
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Canon EOS R5 |
E775608
|
entity |
| Predicate | supportsCanonLog |
P207276
|
FINISHED |
| Object | C-Log |
—
|
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: C-Log | Statement: [Canon EOS R5, supportsCanonLog, C-Log]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: supportsCanonLog Context triple: [Canon EOS R5, supportsCanonLog, C-Log]
-
A.
supportsProResLogEncoding
Indicates that one entity provides or enables ProRes Log encoding functionality for another entity or within a given context.
-
B.
usesCanon
Indicates that one entity employs or relies on another entity as its standard, reference, or authoritative source.
-
C.
supportsColorSampling
Indicates that one entity can perform or accommodate color sampling operations on another entity or its data.
-
D.
supportsAppleProRAW
Indicates that one entity provides compatibility with or functionality for capturing, processing, or handling Apple ProRAW image format for another entity.
-
E.
supportsProResVideo
Indicates that one entity provides the capability for another entity to record, process, or handle video in the ProRes format.
- 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_69f22497341481909c21ba329fadaa6b |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_6a037c9141dc819098d7fcc36e69882c |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a0379e2fac0819089b522db3260028c |
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, 8:12 p.m.