Triple
T6095126
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | General Electric GEnx |
E135857
|
entity |
| Predicate | noiseComparedToPredecessor |
P44406
|
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: [General Electric GEnx, noiseComparedToPredecessor, reduced]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: noiseComparedToPredecessor Context triple: [General Electric GEnx, noiseComparedToPredecessor, reduced]
-
A.
noiseLevel
Indicates the intensity or amount of sound present in a given environment or from a specific source.
-
B.
noiseCompliance
Indicates that an entity adheres to specified rules or standards governing acceptable noise levels or sound emissions.
-
C.
hasNoisePerformance
chosen
Indicates the degree to which one entity’s operation or behavior produces or is characterized by a certain level or quality of noise.
-
D.
hasHeavierSoundThan
Indicates that one entity produces or is associated with a sound that is sonically heavier, more intense, or more forceful than that of another entity.
-
E.
frequencyComparedTo
Indicates how often one event or action occurs relative to another, expressing a comparison of their frequencies.
- 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_69c0087cd3c48190b459848c72d84eb1 |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c05a963bac8190bc0c33fef187875c |
completed | March 22, 2026, 9:09 p.m. |
| PD | Predicate disambiguation | batch_69c049f5ac988190b62ba565153aaa35 |
completed | March 22, 2026, 7:58 p.m. |
Created at: March 22, 2026, 4:12 p.m.