Triple
T23141056
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Boeing 737 MAX 7 |
E577460
|
entity |
| Predicate | noiseLevelComparedToPredecessor |
P82043
|
FINISHED |
| Object | lower |
—
|
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: lower | Statement: [Boeing 737 MAX 7, noiseLevelComparedToPredecessor, lower]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: noiseLevelComparedToPredecessor Context triple: [Boeing 737 MAX 7, noiseLevelComparedToPredecessor, lower]
-
A.
noiseLevel
Indicates the intensity or amount of sound present in a given environment or from a specific source.
-
B.
detailLevelComparedToPredecessor
Indicates how the level of detail of an entity compares to that of its immediate predecessor (e.g., more detailed, less detailed, or similar).
-
C.
hasGreaterNoiseReductionThan
Indicates that one entity provides a higher level of noise reduction compared to another entity.
-
D.
comparedToPredecessor
chosen
Indicates that something is being evaluated or measured in relation to the thing that came immediately before it.
-
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_69e245f8e6248190ba3d58e068b4dccb |
completed | April 17, 2026, 2:38 p.m. |
| NER | Named-entity recognition | batch_69f18eca8a9081908dcc39409f615b7c |
completed | April 29, 2026, 4:53 a.m. |
| PD | Predicate disambiguation | batch_69ef89f83b108190aaaa1db6221fc163 |
completed | April 27, 2026, 4:08 p.m. |
Created at: April 17, 2026, 4 p.m.