Triple
T757350
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fábrica de Aviones Hispano Aviación |
E15585
|
entity |
| Predicate | roleInSector |
P8439
|
FINISHED |
| Object | key player in Spanish military aviation |
—
|
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: key player in Spanish military aviation | Statement: [Fábrica de Aviones Hispano Aviación, roleInSector, key player in Spanish military aviation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: roleInSector Context triple: [Fábrica de Aviones Hispano Aviación, roleInSector, key player in Spanish military aviation]
-
A.
roleInIndustry
chosen
Indicates the specific function, position, or capacity an entity holds within a particular industry or sector.
-
B.
positionInIndustry
Indicates the role, rank, or standing that 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.
positionInWork
Indicates the specific role, rank, or placement an entity holds within a larger work or structured composition.
-
E.
roleInEcosystem
Indicates the specific function or contribution an entity has within an ecosystem and how it interacts with other components of that 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_69a493599a0081908da65f3407af1ef2 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a66ab4608190afcd81e6606c5116 |
completed | March 1, 2026, 8:49 p.m. |
| PD | Predicate disambiguation | batch_69a4a50348088190873a1446db657a78 |
completed | March 1, 2026, 8:43 p.m. |
Created at: March 1, 2026, 7:37 p.m.