Triple
T936802
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Champs-Élysées–Clemenceau |
E20213
|
entity |
| Predicate | isInterchangeStation |
P15892
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Champs-Élysées–Clemenceau, isInterchangeStation, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isInterchangeStation Context triple: [Champs-Élysées–Clemenceau, isInterchangeStation, true]
-
A.
interchangeStation
chosen
Indicates a station where passengers can transfer between different routes, lines, or modes of transportation.
-
B.
hasRailStation
Indicates that one entity possesses, contains, or is served by a rail station.
-
C.
hasBusInterchange
Indicates that one transport-related entity includes, contains, or is associated with a bus interchange facility.
-
D.
hasRailwayStation
Indicates that a place or location is served by, or contains, a railway station.
-
E.
isTransportHubBetween
Indicates that a location functions as a central node facilitating transportation connections between two or more other places.
- 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_69a493b0270c81909e6c9ce310f6aa55 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4b3668a3c8190b0152166efa93ee1 |
completed | March 1, 2026, 9:45 p.m. |
| PD | Predicate disambiguation | batch_69a4b29b245c8190b143f28b77fede3c |
completed | March 1, 2026, 9:41 p.m. |
Created at: March 1, 2026, 7:40 p.m.