Triple
T20158833
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | VAL 206 |
E491648
|
entity |
| Predicate | usedOn |
P2367
|
FINISHED |
| Object | Toulouse Metro |
—
|
NE NERFINISHED |
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: Toulouse Metro | Statement: [VAL 206, usedOn, Toulouse Metro]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Toulouse Metro Context triple: [VAL 206, usedOn, Toulouse Metro]
-
A.
Toulouse Metro
chosen
The Toulouse Metro is a rapid transit system serving the city of Toulouse, France, featuring automated lines that connect key urban and suburban areas.
-
B.
Toulouse Metro Line A
Toulouse Metro Line A is a major rapid transit line in the Toulouse Métro system, running east–west across the city and connecting central Toulouse with suburban areas including Balma.
-
C.
Toulouse Metro Line B
Toulouse Metro Line B is a major automated rapid transit line in the Toulouse Metro system in France, running north–south through the city and serving key residential, commercial, and university areas.
-
D.
Marseille metro
The Marseille metro is the rapid transit system serving the city of Marseille, France, providing underground rail connections across key urban areas.
-
E.
Lyon Metro
Lyon Metro is the rapid transit system serving the French city of Lyon and its suburbs, known for its rubber-tyred lines and integration with the city’s broader public transport network.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69da6266c6888190bc1a3ecf24814d34 |
completed | April 11, 2026, 3:01 p.m. |
| NER | Named-entity recognition | batch_69e667e27aa88190a326288b992ea274 |
completed | April 20, 2026, 5:52 p.m. |
Created at: April 11, 2026, 11:34 p.m.