Triple
T32360062
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Filton and Bradley Stoke |
E826834
|
entity |
| Predicate | containsMajorEmployer |
P588
|
FINISHED |
| Object | Airbus Filton |
—
|
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 Filton | Statement: [Filton and Bradley Stoke, containsMajorEmployer, Airbus Filton]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: containsMajorEmployer Context triple: [Filton and Bradley Stoke, containsMajorEmployer, Airbus Filton]
-
A.
hasMajorEmployer
chosen
Indicates that an entity has a primary or most significant employer with which it is chiefly affiliated for work or occupation.
-
B.
hasMajorEmployerType
Indicates the type or category of major employer associated with an entity.
-
C.
isMajorEmployerLocationIn
Indicates that a location is a primary or significant site where an employer conducts its employment activities or has a major workforce presence.
-
D.
hasMajorEmployerHistory
Indicates that an entity has a documented history of employment with a major or significant employer.
-
E.
isOneOfLargestEmployers
Indicates that an entity ranks among the largest organizations in terms of the number of people it employs.
- 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_69f34915a2588190bb3178f5ec2f48f4 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69ffc605b0648190a7abe9128b0d857a |
completed | May 9, 2026, 11:40 p.m. |
| PD | Predicate disambiguation | batch_69ffc5742d80819099f947ece78d5700 |
completed | May 9, 2026, 11:38 p.m. |
Created at: May 1, 2026, 12:49 a.m.