Triple
T15779258
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lyon Metro line D |
E382568
|
entity |
| Predicate | connectsAt |
P1139
|
FINISHED |
| Object | Gare de Vaise |
E1181270
|
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: Gare de Vaise | Statement: [Lyon Metro line D, connectsAt, Gare de Vaise]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gare de Vaise Context triple: [Lyon Metro line D, connectsAt, Gare de Vaise]
-
A.
Gare de Vaise
chosen
Gare de Vaise is a major transport hub and metro terminus in Lyon, France, serving the northwestern part of the city.
-
B.
Gare de Vénissieux
Gare de Vénissieux is a major transport hub in the Lyon metropolitan area, serving as both a railway station and a key terminus for the city’s metro and tram networks.
-
C.
Gare de Colombes
Gare de Colombes is a suburban railway station in Colombes, France, serving regional commuter trains in the Paris metropolitan area.
-
D.
Gare d’Oullins
Gare d’Oullins is a railway and metro station in the suburb of Oullins near Lyon, France, serving as a key public transport hub integrated into the Lyon Metro network.
-
E.
Gare de Javel
Gare de Javel is a Parisian commuter rail station in the 15th arrondissement that serves local and regional passengers along the Seine.
- 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_69d86da09a10819082fe9797b23e4664 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e053fea90081908e3fe4f91475bead |
completed | April 16, 2026, 3:14 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffb59779788190a393237f5293fe8d |
completed | May 9, 2026, 10:30 p.m. |
Created at: April 10, 2026, 4:48 a.m.