Triple
T25715385
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | London–Sydney |
E644847
|
entity |
| Predicate | hasBeenOperatedViaStopover |
P138842
|
FINISHED |
| Object | Darwin |
—
|
NE NERFINISHED |
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: Darwin | Statement: [London–Sydney, hasBeenOperatedViaStopover, Darwin]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBeenOperatedViaStopover Context triple: [London–Sydney, hasBeenOperatedViaStopover, Darwin]
-
A.
hasStopoverState
Indicates that an entity’s journey or process includes an intermediate stop or temporary state before reaching its final destination or outcome.
-
B.
aircraftStopover
Indicates that an aircraft makes an intermediate stop at a specific location during its journey between origin and final destination.
-
C.
stopoverAirport
Indicates that an itinerary or flight includes a particular airport as an intermediate stop between the origin and final destination.
-
D.
stopoverCountry
Indicates that a journey or flight includes an intermediate stop in a specified country before reaching its final destination.
-
E.
stopoverLocation
chosen
Indicates that an entity makes an intermediate stop or layover at a specified location during a journey or route.
- 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_69e77e8476fc8190bd5e9d05b89fad0a |
completed | April 21, 2026, 1:41 p.m. |
| NER | Named-entity recognition | batch_69f63fd6c68481908c542aa03e297b9c |
completed | May 2, 2026, 6:17 p.m. |
| PD | Predicate disambiguation | batch_69f63c6456608190b94e7c2e2c2a4824 |
completed | May 2, 2026, 6:03 p.m. |
Created at: April 21, 2026, 9:40 p.m.