Triple
T661388
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | TGV |
E11761
|
entity |
| Predicate | hasDirectAirportLink |
P4363
|
FINISHED |
| Object | Charles de Gaulle Airport – nationwide destinations |
—
|
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: Charles de Gaulle Airport – nationwide destinations | Statement: [TGV, hasDirectAirportLink, Charles de Gaulle Airport – nationwide destinations]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDirectAirportLink Context triple: [TGV, hasDirectAirportLink, Charles de Gaulle Airport – nationwide destinations]
-
A.
hasCityPair
Indicates a relationship that links two cities considered as a connected or associated pair, often for purposes such as travel, trade, or comparison.
-
B.
airportServesAs
Indicates that an airport functions in a particular role or capacity (such as primary, secondary, or hub) for a specified area, organization, or service.
-
C.
hasInternationalAirport
Indicates that a place possesses an airport that handles international flights and services cross-border air traffic.
-
D.
associatedWithAirportName
Indicates a relationship where an entity is linked or connected to a specific airport by its name.
-
E.
airportServed
chosen
Indicates that a particular airport provides service to, or is used for air travel to and from, a given location or area.
- 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_69a4932862a0819098be659c814e4981 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a4a0f55f7481909e052a25bd12d455 |
completed | March 1, 2026, 8:26 p.m. |
| PD | Predicate disambiguation | batch_69a49d1406ec8190abf546549264c85d |
completed | March 1, 2026, 8:09 p.m. |
Created at: March 1, 2026, 7:36 p.m.