Triple
T13335669
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Edgar Schmued |
E317684
|
entity |
| Predicate | aircraftCategorySpecialization |
P70650
|
FINISHED |
| Object | fighter aircraft |
—
|
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: fighter aircraft | Statement: [Edgar Schmued, aircraftCategorySpecialization, fighter aircraft]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: aircraftCategorySpecialization Context triple: [Edgar Schmued, aircraftCategorySpecialization, fighter aircraft]
-
A.
aircraftRoleSpecialization
Indicates that one aircraft role is a more specific, specialized form of another, more general aircraft role.
-
B.
typicalAircraftTypeCategory
Indicates the general class or category of aircraft type that is most commonly associated with or used in a given context.
-
C.
aircraftSpeedClass
Indicates the categorical speed range or performance class to which an aircraft’s speed belongs.
-
D.
aircraftCategoryProduced
Indicates that an entity (such as a manufacturer or organization) has produced aircraft belonging to a specified aircraft category.
-
E.
planeCategory
chosen
Indicates the classification or type of a plane within a defined categorization scheme.
- 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_69d806b5a3c08190b42c267fb092f98a |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d99d00b75c8190af98784c7df904c8 |
completed | April 11, 2026, 12:59 a.m. |
| PD | Predicate disambiguation | batch_69d98f6e53d88190bd6aa42f69b10ffb |
completed | April 11, 2026, 12:01 a.m. |
Created at: April 9, 2026, 9:30 p.m.