Triple
T2987464
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dolby Vision |
E80660
|
entity |
| Predicate | metadataType |
P44503
|
FINISHED |
| Object | dynamic HDR metadata |
—
|
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: dynamic HDR metadata | Statement: [Dolby Vision, metadataType, dynamic HDR metadata]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: metadataType Context triple: [Dolby Vision, metadataType, dynamic HDR metadata]
-
A.
datumType
Indicates the specific kind or category of data that characterizes or classifies a datum.
-
B.
metaProperty
Indicates that one property functions as a higher-level descriptor or attribute about another property, rather than about an entity directly.
-
C.
metricType
Indicates the specific category or kind of measurement that a given metric represents.
-
D.
semanticType
Indicates that something belongs to or is categorized under a particular semantic class or type based on its meaning.
-
E.
dataTypes
Indicates that one entity specifies or defines the kinds or formats of data that are valid or expected 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_69ad8b16c3488190b47b6aa7a59a335b |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad99c88f608190bf734e0b744bf3d1 |
completed | March 8, 2026, 3:46 p.m. |
| PD | Predicate disambiguation | batch_69ad961403108190bbecb8d3608fd4e0 |
completed | March 8, 2026, 3:30 p.m. |
| PDg | Predicate description generation | batch_69ad97f5d28c8190899d90204dc43428 |
completed | March 8, 2026, 3:38 p.m. |
Created at: March 8, 2026, 2:59 p.m.