Triple
T1892962
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Concorde (Air France) |
E41912
|
entity |
| Predicate | airlineLivery |
P21786
|
FINISHED |
| Object | Air France livery |
—
|
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: Air France livery | Statement: [Concorde (Air France), airlineLivery, Air France livery]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: airlineLivery Context triple: [Concorde (Air France), airlineLivery, Air France livery]
-
A.
hasLivery
chosen
Indicates that one entity bears or displays the distinctive colors, markings, or branding (livery) associated with another entity.
-
B.
liveryFeature
Indicates a characteristic or design element that is part of a specific livery or external appearance scheme.
-
C.
aircraftMarking
Indicates a relationship where a marking, symbol, or identifier is applied to or displayed on an aircraft.
-
D.
carrierAircraft
Indicates that an aircraft is designed, equipped, or used to operate from an aircraft carrier.
-
E.
aircraftConfiguration
Indicates the specific arrangement or setup of an aircraft’s components, systems, or features for a given purpose or operating condition.
- 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_69a8864b6de0819098d089f6a1b910a7 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69abb1480a6c81909fcf5cce4c42fed4 |
completed | March 7, 2026, 5:02 a.m. |
| PD | Predicate disambiguation | batch_69abafe7e7e88190b58c0df59187c0c2 |
completed | March 7, 2026, 4:56 a.m. |
Created at: March 4, 2026, 7:34 p.m.