Triple
T12935118
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dolby A |
E309487
|
entity |
| Predicate | dynamicRangeImprovement |
P86658
|
FINISHED |
| Object | approximately 10 dB |
—
|
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: approximately 10 dB | Statement: [Dolby A, dynamicRangeImprovement, approximately 10 dB]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: dynamicRangeImprovement Context triple: [Dolby A, dynamicRangeImprovement, approximately 10 dB]
-
A.
supportsHighDynamicRangeAudio
chosen
Indicates that an entity is capable of handling or providing audio with a high dynamic range, preserving a wide span between the quietest and loudest sounds.
-
B.
hasGreaterNoiseReductionThan
Indicates that one entity provides a higher level of noise reduction compared to another entity.
-
C.
contrastEffect
Indicates that one entity’s characteristics are perceived or evaluated differently because they are compared or juxtaposed with another entity.
-
D.
noiseReductionFeature
Indicates that an entity includes or supports a capability to reduce or minimize unwanted noise.
-
E.
noiseReductionGoal
Indicates the intended target level or objective for reducing noise in a given context or system.
- 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_69d7bdfa933c8190b5a27aa4a08a19b7 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d97e59a4c88190907d05b8d57dae89 |
completed | April 10, 2026, 10:48 p.m. |
| PD | Predicate disambiguation | batch_69d97db69f548190a1a693bc0d6c191a |
completed | April 10, 2026, 10:46 p.m. |
Created at: April 9, 2026, 5:42 p.m.