Triple
T19485140
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lyon Metro |
E487491
|
entity |
| Predicate | servesAirportIndirectly |
P6864
|
FINISHED |
| Object | Lyon–Saint-Exupéry Airport via Rhônexpress |
—
|
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: Lyon–Saint-Exupéry Airport via Rhônexpress | Statement: [Lyon Metro, servesAirportIndirectly, Lyon–Saint-Exupéry Airport via Rhônexpress]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: servesAirportIndirectly Context triple: [Lyon Metro, servesAirportIndirectly, Lyon–Saint-Exupéry Airport via Rhônexpress]
-
A.
servesAirport
chosen
Indicates that a transportation service or route provides access to and operates for a particular airport.
-
B.
servesAirportIATA
Indicates that a transportation service or facility operates routes to or from the airport identified by the given IATA code.
-
C.
associatedAirportServes
Indicates that a given airport provides service to, or is used by, the associated entity (such as a city, region, or facility).
-
D.
servesAirportICAO
Indicates that a transportation service or facility operates routes to or from the airport identified by the given ICAO code.
-
E.
servesFlightsTo
Indicates that one transportation provider regularly operates flights to a specified destination location.
- 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_69d8e8d924388190b847cb15bb3d0aff |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e6343dcc748190b0df816e6ab4cafb |
completed | April 20, 2026, 2:12 p.m. |
| PD | Predicate disambiguation | batch_69e4fd7883308190b73912a71a35a835 |
completed | April 19, 2026, 4:06 p.m. |
Created at: April 10, 2026, 1:39 p.m.