Triple
T10847393
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Paris–Rennes railway |
E256048
|
entity |
| Predicate | endStation |
P3569
|
FINISHED |
| Object | Rennes station |
E341551
|
NE 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: Rennes station | Statement: [Paris–Rennes railway, endStation, Rennes station]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rennes station Context triple: [Paris–Rennes railway, endStation, Rennes station]
-
A.
Rennes railway station
chosen
Rennes railway station is the main rail hub of the city of Rennes in western France, serving high-speed TGV, regional, and local train services.
-
B.
Clermont-Ferrand station
Clermont-Ferrand station is the main railway station serving the city of Clermont-Ferrand in central France, acting as a key regional hub for passenger rail services.
-
C.
Gare de Nantes
Gare de Nantes is the main railway station serving the city of Nantes in western France, providing regional and high-speed train connections.
-
D.
Lyon station
Lyon station is an underground light rail transit station in downtown Ottawa, Canada, serving the city’s O-Train Confederation Line.
-
E.
Reims station
Reims station is the main railway station serving the city of Reims in northeastern France, providing regional and high-speed train connections.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d6aa81a5d08190aa86689061d1ddd2 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d75113bc188190ac78df0c51d95de6 |
completed | April 9, 2026, 7:11 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e23b7578688190975c087d28808be5 |
completed | April 17, 2026, 1:53 p.m. |
Created at: April 8, 2026, 9:20 p.m.