Triple
T3986775
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dolby TrueHD |
E86890
|
entity |
| Predicate | audioCodingType |
P53672
|
FINISHED |
| Object | lossless |
—
|
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: lossless | Statement: [Dolby TrueHD, audioCodingType, lossless]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: audioCodingType Context triple: [Dolby TrueHD, audioCodingType, lossless]
-
A.
recordingType
Indicates the specific kind or category of recording associated with an entity (e.g., audio, video, live, studio, etc.).
-
B.
supportsAudioQuality
Indicates that one entity provides or is compatible with a specified level or type of audio quality for another entity or context.
-
C.
audioChannels
Indicates the number or configuration of distinct audio signal paths (such as mono, stereo, or surround) used in a recording, transmission, or playback.
-
D.
codeType
Indicates the classification or category assigned to a particular code within a coding or encoding system.
-
E.
audioSampleRateHz
Indicates the number of audio samples captured or played back per second, measured in hertz (Hz), for the associated audio data.
- 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_69aed93fd9d4819085d3b2137d2346cb |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefb81040481909b22e4c445ecae0f |
completed | March 9, 2026, 4:55 p.m. |
| PD | Predicate disambiguation | batch_69aef8f692008190bf4d637ffc3d3eaa |
completed | March 9, 2026, 4:44 p.m. |
| PDg | Predicate description generation | batch_69aefb7f92348190ae35f1d75b0b5d4f |
completed | March 9, 2026, 4:55 p.m. |
Created at: March 9, 2026, 3:33 p.m.