Triple
T1721946
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | CASA |
E37410
|
entity |
| Predicate | roleInEuropeanAerospace |
P8439
|
FINISHED |
| Object | founding partner in Airbus military programs |
—
|
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: founding partner in Airbus military programs | Statement: [CASA, roleInEuropeanAerospace, founding partner in Airbus military programs]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: roleInEuropeanAerospace Context triple: [CASA, roleInEuropeanAerospace, founding partner in Airbus military programs]
-
A.
roleWithinRaytheon
Indicates that one entity holds or has held a specific role, position, or function within the organization Raytheon.
-
B.
roleInIndustry
chosen
Indicates the specific function, position, or capacity an entity holds within a particular industry or sector.
-
C.
roleInvolves
Indicates that a particular role includes or requires participation in a specified activity, responsibility, or function.
-
D.
hasOrganizationalRole
Indicates that an entity holds a specific role, position, or function within an organization.
-
E.
personnelType
Indicates the classification or role category assigned to a person within an organization or system.
- 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_69a8861acab88190bb43cde203429399 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69aadb7bda1081908f2c41c520c9c55c |
completed | March 6, 2026, 1:49 p.m. |
| PD | Predicate disambiguation | batch_69aa61c0a0288190bce9d60062a84b69 |
completed | March 6, 2026, 5:10 a.m. |
Created at: March 4, 2026, 7:30 p.m.