Triple
T30240277
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Santos-Dumont No. 5 |
E768892
|
entity |
| Predicate | locationOfFlights |
P85995
|
FINISHED |
| Object | Paris |
—
|
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: Paris | Statement: [Santos-Dumont No. 5, locationOfFlights, Paris]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: locationOfFlights Context triple: [Santos-Dumont No. 5, locationOfFlights, Paris]
-
A.
flightHub
Indicates a central location or system from which multiple flights are coordinated, managed, or connected.
-
B.
testFlightLocation
chosen
Indicates the location where a test flight takes place or is conducted.
-
C.
servesFlightsTo
Indicates that one transportation provider regularly operates flights to a specified destination location.
-
D.
airportLocatedWithin
Indicates that an airport is geographically situated inside the boundaries of a specified area or region.
-
E.
flightRoute
Indicates a path or sequence of locations that a particular flight travels between, typically from its origin to its destination (and possibly via intermediate stops).
- 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_69f224820c048190b1435c4cc145acf1 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_6a00ada2903481908b28ce55ef97a6c2 |
completed | May 10, 2026, 4:09 p.m. |
| PD | Predicate disambiguation | batch_6a00ad5d23788190b3f9e2de761d39bb |
completed | May 10, 2026, 4:07 p.m. |
Created at: April 29, 2026, 7:38 p.m.