Triple
T8926911
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ATSC 3.0 |
E212558
|
entity |
| Predicate | supportsHighDynamicRange |
P48295
|
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: [ATSC 3.0, supportsHighDynamicRange, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: supportsHighDynamicRange Context triple: [ATSC 3.0, supportsHighDynamicRange, true]
-
A.
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.
-
B.
supportsHDRStandard
chosen
Indicates that one entity is compatible with and can correctly handle or implement a specified HDR (High Dynamic Range) standard defined by another entity.
-
C.
supportsDolbyVisionHDRRecording
Indicates that the subject is capable of recording video content using the Dolby Vision high dynamic range (HDR) format.
-
D.
supportsColorSampling
Indicates that one entity can perform or accommodate color sampling operations on another entity or its data.
-
E.
supportsWideColorGamut
Indicates that one entity provides or enables compatibility with a wide color gamut capability for another entity or context.
- 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_69ca839481d48190b42b037e0d0f636c |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc6671557c81909f3837ffd6a15ffe |
completed | April 1, 2026, 12:27 a.m. |
| PD | Predicate disambiguation | batch_69cc5ed3286c8190a21de2ee11f2639f |
completed | March 31, 2026, 11:54 p.m. |
Created at: March 30, 2026, 6:57 p.m.