Triple
T21627439
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | AY-3-8912 |
E533738
|
entity |
| Predicate | hasNoiseGenerator |
P145283
|
FINISHED |
| Object | pseudo-random noise |
—
|
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: pseudo-random noise | Statement: [AY-3-8912, hasNoiseGenerator, pseudo-random noise]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNoiseGenerator Context triple: [AY-3-8912, hasNoiseGenerator, pseudo-random noise]
-
A.
hasNoiseTerm
Indicates that a given expression, model, or equation includes an additional noise term representing random or unexplained variation.
-
B.
hasNoiseModes
Indicates that an entity supports or is associated with one or more distinct noise-related operating modes or settings.
-
C.
hasNoiseContext
Indicates that an entity is associated with or occurs within a particular noise-related environment or acoustic condition.
-
D.
hasRealWorldNoise
Indicates that the subject includes or is affected by noise or variability originating from real-world conditions rather than idealized or simulated data.
-
E.
hasNoisePerformance
Indicates the degree to which one entity’s operation or behavior produces or is characterized by a certain level or quality of noise.
- 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_69e0c464fba881908d0ff2ac80511ce1 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69ef52141e1c8190a861f4bc7cfcb490 |
completed | April 27, 2026, 12:09 p.m. |
| PD | Predicate disambiguation | batch_69e69677b9c48190bf81f795aa8ad74e |
completed | April 20, 2026, 9:11 p.m. |
| PDg | Predicate description generation | batch_69e69cb4bcbc8190a4fc2d508df107be |
completed | April 20, 2026, 9:37 p.m. |
Created at: April 16, 2026, 6:34 p.m.