Triple
T1815025
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Airbus A220 |
E40416
|
entity |
| Predicate | firstCommercialService |
P1929
|
FINISHED |
| Object | July 2016 |
—
|
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: July 2016 | Statement: [Airbus A220, firstCommercialService, July 2016]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: firstCommercialService Context triple: [Airbus A220, firstCommercialService, July 2016]
-
A.
firstCommercialUse
chosen
Indicates the earliest point in time at which something was used commercially or put into commercial operation.
-
B.
primaryService
Indicates that one entity serves as the main or principal service provided or used in relation to another entity.
-
C.
firstFlightService
Indicates that an entity operates or provides service on the earliest scheduled flight in a given context or route.
-
D.
locationOfFirstCommercialUse
Indicates the place where something was first used commercially.
-
E.
firstUsedFor
Indicates that one entity was the earliest or original thing for which another entity was used or applied.
- 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_69a8864526c081908a3a4d74f689e2c5 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69aba67721788190951beae25e885457 |
completed | March 7, 2026, 4:15 a.m. |
| PD | Predicate disambiguation | batch_69aa61d884548190a19cf3a6b5ae9d48 |
completed | March 6, 2026, 5:10 a.m. |
Created at: March 4, 2026, 7:32 p.m.