Triple
T30481867
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Canon EOS R5 |
E775608
|
entity |
| Predicate | supportsHDRPQ |
P49172
|
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: [Canon EOS R5, supportsHDRPQ, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: supportsHDRPQ Context triple: [Canon EOS R5, supportsHDRPQ, true]
-
A.
supportsHDRStandard
Indicates that one entity is compatible with and can correctly handle or implement a specified HDR (High Dynamic Range) standard defined by another entity.
-
B.
supportsHDRFormat
chosen
Indicates that one entity is capable of handling, displaying, or processing content encoded in a specified High Dynamic Range (HDR) format for another entity.
-
C.
supportsSmartHDR
Indicates that an entity is capable of handling or enabling Smart HDR (High Dynamic Range) functionality.
-
D.
supportsHardwareRayTracing
Indicates that one entity provides or enables hardware-level ray tracing capabilities for another entity or within a given context.
-
E.
supportsHighDynamicRangeAudio
Indicates that an entity is capable of handling or providing audio with a high dynamic range, preserving a wide span between the quietest and loudest sounds.
- 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_69f22497341481909c21ba329fadaa6b |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_6a037c876524819098545e6037d3107d |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a0379e2fac0819089b522db3260028c |
completed | May 12, 2026, 7:05 p.m. |
Created at: April 29, 2026, 8:12 p.m.