Triple
T1892950
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Concorde (Air France) |
E41912
|
entity |
| Predicate | typicalTransatlanticFlightTime |
P1526
|
FINISHED |
| Object | about 3.5 hours Paris–New York |
—
|
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: about 3.5 hours Paris–New York | Statement: [Concorde (Air France), typicalTransatlanticFlightTime, about 3.5 hours Paris–New York]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalTransatlanticFlightTime Context triple: [Concorde (Air France), typicalTransatlanticFlightTime, about 3.5 hours Paris–New York]
-
A.
flightDuration
chosen
Indicates the length of time that a specific flight takes from departure to arrival.
-
B.
airTime
Indicates the duration or scheduling time during which something, typically a broadcast or performance, is transmitted or presented.
-
C.
voyageDuration
Indicates the length of time that a voyage or journey lasts from its start to its end.
-
D.
flightRegime
Indicates the operational conditions or phase of flight under which an aircraft or aerospace vehicle is functioning (e.g., speed, altitude, and atmospheric regime).
-
E.
airTraffic
Indicates the movement and flow of aircraft through airspace, including their routes, density, and interactions while in flight.
- 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.