Triple
T3003080
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pixel 6a |
E81834
|
entity |
| Predicate | hasHDRSupport |
P182
|
FINISHED |
| Object | HDR |
—
|
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: HDR | Statement: [Pixel 6a, hasHDRSupport, HDR]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasHDRSupport Context triple: [Pixel 6a, hasHDRSupport, HDR]
-
A.
supportsColorSampling
Indicates that one entity can perform or accommodate color sampling operations on another entity or its data.
-
B.
supportsWideColorGamut
Indicates that one entity provides or enables compatibility with a wide color gamut capability for another entity or context.
-
C.
supportsDolbyVisionHDRRecording
Indicates that the subject is capable of recording video content using the Dolby Vision high dynamic range (HDR) format.
-
D.
supportsHEVCEncode
Indicates that one entity provides the capability for another entity to perform HEVC (High Efficiency Video Coding) encoding.
-
E.
hasFeature
chosen
Indicates that an entity possesses, exhibits, or includes a particular characteristic, attribute, or component.
- 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_69ad8b1c4de88190a83b7cefaa1f2842 |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad9a1371c481909e214234afed1a65 |
completed | March 8, 2026, 3:47 p.m. |
| PD | Predicate disambiguation | batch_69ad96180eb08190a524c5f458d41382 |
completed | March 8, 2026, 3:30 p.m. |
Created at: March 8, 2026, 2:59 p.m.