Triple
T38222123
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | dbx noise reduction |
E1012037
|
entity |
| Predicate | encodingProcess |
P190319
|
FINISHED |
| Object | compresses dynamic range before recording |
—
|
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: compresses dynamic range before recording | Statement: [dbx noise reduction, encodingProcess, compresses dynamic range before recording]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: encodingProcess Context triple: [dbx noise reduction, encodingProcess, compresses dynamic range before recording]
-
A.
encodingStage
Indicates the specific phase or step within an encoding process at which a given action, transformation, or state occurs.
-
B.
encodes
Indicates that one entity contains or represents the information, instructions, or structure of another in a coded or symbolic form.
-
C.
encodingStatus
Indicates the current state or progress of an encoding process applied to some content or data.
-
D.
encodingAbstraction
Indicates an abstraction relationship where one representation or model encodes, summarizes, or symbolically captures the structure or information content of another.
-
E.
encodingLibrary
Indicates that one entity is the software library or tool used to encode, transform, or serialize the other entity’s data or content.
- 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_69f76dd25e0c81909f2abd0803e5e3ee |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69fcc42cbac48190b8d3e4c9ce140838 |
completed | May 7, 2026, 4:56 p.m. |
| PD | Predicate disambiguation | batch_69fcb0fc69c88190800453eb57a7e62c |
completed | May 7, 2026, 3:34 p.m. |
| PDg | Predicate description generation | batch_69fcc42b9334819099929649b7ef68ea |
completed | May 7, 2026, 4:56 p.m. |
Created at: May 3, 2026, 4:30 p.m.