Triple
T29448089
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | A220 series |
E746903
|
entity |
| Predicate | noiseFootprint |
P167197
|
FINISHED |
| Object | reduced |
—
|
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: reduced | Statement: [A220 series, noiseFootprint, reduced]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: noiseFootprint Context triple: [A220 series, noiseFootprint, reduced]
-
A.
noiseCompliance
Indicates that an entity adheres to specified rules or standards governing acceptable noise levels or sound emissions.
-
B.
noiseLevel
Indicates the intensity or amount of sound present in a given environment or from a specific source.
-
C.
noiseSource
Indicates that one entity is the origin or producer of a particular noise affecting another entity or the environment.
-
D.
noisePolicy
Indicates the rules or constraints governing acceptable noise levels or noise-related behavior in a given context.
-
E.
targetsNoiseType
Indicates that an entity is directed at, designed for, or specifically affects a particular type or category 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_69f0a7a230488190b44a97fe3d16f731 |
completed | April 28, 2026, 12:27 p.m. |
| NER | Named-entity recognition | batch_69f66b22beec8190978f4cf0f602fc20 |
completed | May 2, 2026, 9:22 p.m. |
| PD | Predicate disambiguation | batch_69f66339175c819080bd70f0ff7057b1 |
completed | May 2, 2026, 8:48 p.m. |
| PDg | Predicate description generation | batch_69f663ff176c8190aaadb475f75daee4 |
completed | May 2, 2026, 8:52 p.m. |
Created at: April 28, 2026, 3:29 p.m.