Triple
T3141760
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Paris–San Francisco |
E65663
|
entity |
| Predicate | approximateNonstopFlightTimeHours |
P1526
|
FINISHED |
| Object | 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: 11 | Statement: [Paris–San Francisco, approximateNonstopFlightTimeHours, 11]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: approximateNonstopFlightTimeHours Context triple: [Paris–San Francisco, approximateNonstopFlightTimeHours, 11]
-
A.
flightDuration
chosen
Indicates the length of time that a specific flight takes from departure to arrival.
-
B.
approximateTravelTimeToSheremetyevo
Indicates the estimated amount of time it typically takes to travel from a given location to Sheremetyevo.
-
C.
approximateTravelTimeToVnukovo
Indicates the estimated duration it typically takes to travel from a given location to Vnukovo.
-
D.
airTime
Indicates the duration or scheduling time during which something, typically a broadcast or performance, is transmitted or presented.
-
E.
voyageDuration
Indicates the length of time that a voyage or journey lasts from its start to its end.
- 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_69ad8582f564819088c27e1f96153938 |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada57895dc8190bd3d4ef9391973dc |
completed | March 8, 2026, 4:36 p.m. |
| PD | Predicate disambiguation | batch_69ad9df840088190a26a1516f4c1f056 |
completed | March 8, 2026, 4:04 p.m. |
Created at: March 8, 2026, 3:05 p.m.