Triple
T30209745
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Airbus Broughton plant |
E768035
|
entity |
| Predicate | producesForModel |
P23178
|
FINISHED |
| Object | Airbus A320 family |
—
|
NE NERFINISHED |
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: Airbus A320 family | Statement: [Airbus Broughton plant, producesForModel, Airbus A320 family]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: producesForModel Context triple: [Airbus Broughton plant, producesForModel, Airbus A320 family]
-
A.
producesFor
chosen
Indicates that one entity creates, manufactures, or generates something specifically intended for another entity’s use, benefit, or distribution.
-
B.
producedModel
Indicates that one entity created, manufactured, or generated the other entity as a model or product.
-
C.
associatedModelGeneration
Indicates that one entity is responsible for creating, producing, or generating another related model or representation.
-
D.
usesProductionModel
Indicates that one entity employs or relies on another entity as its primary or official production model in practice.
-
E.
introducedForModel
Indicates that one entity was created, proposed, or brought into use specifically for application within a particular model.
- 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_69f2247eb0848190b4032f302d39c0d9 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69fd3a69f1e08190a11aed015bff0858 |
completed | May 8, 2026, 1:20 a.m. |
| PD | Predicate disambiguation | batch_69fd39124180819080ca7911d3515d6d |
completed | May 8, 2026, 1:14 a.m. |
Created at: April 29, 2026, 7:32 p.m.