Triple
T38209995
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | High Com noise reduction |
E1010511
|
entity |
| Predicate | noiseTypeReduced |
P107588
|
FINISHED |
| Object | tape hiss |
—
|
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: tape hiss | Statement: [High Com noise reduction, noiseTypeReduced, tape hiss]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: noiseTypeReduced Context triple: [High Com noise reduction, noiseTypeReduced, tape hiss]
-
A.
noiseReductionType
chosen
Indicates the specific method or technique used to reduce or minimize noise in a given context.
-
B.
noiseReductionFeature
Indicates that an entity includes or supports a capability to reduce or minimize unwanted noise.
-
C.
noiseReductionGoal
Indicates the intended target level or objective for reducing noise in a given context or system.
-
D.
noiseLevel
Indicates the intensity or amount of sound present in a given environment or from a specific source.
-
E.
noiseCompliance
Indicates that an entity adheres to specified rules or standards governing acceptable noise levels or sound emissions.
- 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_69f76dcdc7708190a5f1751d53f40ffe |
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. |
Created at: May 3, 2026, 4:30 p.m.