Triple
T3078579
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dolby Digital |
E64199
|
entity |
| Predicate | maximumBitrate |
P45736
|
FINISHED |
| Object | 640 kbit/s |
—
|
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: 640 kbit/s | Statement: [Dolby Digital, maximumBitrate, 640 kbit/s]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: maximumBitrate Context triple: [Dolby Digital, maximumBitrate, 640 kbit/s]
-
A.
maximumResolution
Indicates the highest level of detail or fineness at which something (such as an image, display, or measurement) can be represented or processed.
-
B.
maxDataTransferMode
Indicates the data transfer mode in which the maximum possible data throughput is achieved between entities.
-
C.
maxSpatialStreams
Indicates the maximum number of simultaneous spatial data streams that can be used or supported in a communication or processing context.
-
D.
maximumBrightness
Indicates the highest level of brightness that an entity can reach or exhibit.
-
E.
maximumVideoLength
Indicates the greatest allowable or supported duration for a video in this context.
- 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_69ad857bb4c88190a4cf27893fcabed8 |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada1a86a848190a47ca127cc7e6326 |
completed | March 8, 2026, 4:19 p.m. |
| PD | Predicate disambiguation | batch_69ad9debb6308190be28378ae1fc98af |
completed | March 8, 2026, 4:03 p.m. |
| PDg | Predicate description generation | batch_69ada0f6fef48190b13898be383a246b |
completed | March 8, 2026, 4:16 p.m. |
Created at: March 8, 2026, 3:02 p.m.