Triple
T8630756
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | A220-100 |
E204394
|
entity |
| Predicate | fuselageVariant |
P84516
|
FINISHED |
| Object | shorter-fuselage variant |
—
|
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: shorter-fuselage variant | Statement: [A220-100, fuselageVariant, shorter-fuselage variant]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fuselageVariant Context triple: [A220-100, fuselageVariant, shorter-fuselage variant]
-
A.
fuselageType
Indicates the specific structural or design category of an aircraft’s fuselage that an entity belongs to or uses.
-
B.
fuselageShape
Indicates the geometric form or contour of an object's fuselage, describing how its main body is shaped.
-
C.
fuselageCount
Indicates the number of fuselages associated with or contained in an aircraft or aerospace structure.
-
D.
specificCarrierAircraftVariant
Indicates that one aircraft variant is a specific version designed or adapted for carrier-based operations of another, more general aircraft variant.
-
E.
fuselageDiameter
Indicates the diameter measurement of an aircraft’s fuselage in the described context.
- F. None of above. chosen
Provenance (4 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_69ca834b903c8190add96cc651e1a477 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc5730309081909a9a0256c9bf5f8f |
completed | March 31, 2026, 11:22 p.m. |
| PD | Predicate disambiguation | batch_69cc455906f8819082edd79cb4a1cf28 |
completed | March 31, 2026, 10:06 p.m. |
| PDg | Predicate description generation | batch_69cc572d99bc819097f36b140c2ee1ce |
completed | March 31, 2026, 11:22 p.m. |
Created at: March 30, 2026, 6:27 p.m.