Triple
T11642588
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Seoul–London |
E276692
|
entity |
| Predicate | typicalNonstopFlightTimeHours |
P1526
|
FINISHED |
| Object | approximately 11 |
—
|
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: approximately 11 | Statement: [Seoul–London, typicalNonstopFlightTimeHours, approximately 11]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalNonstopFlightTimeHours Context triple: [Seoul–London, typicalNonstopFlightTimeHours, approximately 11]
-
A.
flightDuration
chosen
Indicates the length of time that a specific flight takes from departure to arrival.
-
B.
isNonStop
Indicates that a service, trip, or process occurs from start to finish without any intermediate stops or interruptions.
-
C.
flightPeriod
Indicates the time span during which a flight occurs or is scheduled to operate.
-
D.
quantityFlown
Indicates the amount or volume that has been transported by flying from one place to another.
-
E.
flightHours
Indicates the number of hours an entity has spent in flight or operating in the air.
- 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_69d6aafbb3c081908a9cdb4ecb8d981d |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8a260ab488190ab1c00d9850f3096 |
completed | April 10, 2026, 7:10 a.m. |
| PD | Predicate disambiguation | batch_69d85dd94bdc819091fa2ed33eb31624 |
completed | April 10, 2026, 2:18 a.m. |
Created at: April 8, 2026, 9:39 p.m.