Triple
T12938071
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | La Doua campus |
E309565
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Villeurbanne |
E96069
|
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: Villeurbanne | Statement: [La Doua campus, locatedIn, Villeurbanne]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Villeurbanne Context triple: [La Doua campus, locatedIn, Villeurbanne]
-
A.
Villeurbanne
chosen
Villeurbanne is a major suburban city adjacent to Lyon in eastern France, known for its dense urban character and role as part of the Lyon metropolitan area.
-
B.
Bois-Colombes
Bois-Colombes is a suburban commune in the northwestern outskirts of Paris, France, known for its residential character and proximity to the capital.
-
C.
Saint-Priest
Saint-Priest is a suburban commune in eastern France that forms part of the metropolitan area of Lyon.
-
D.
Firminy
Firminy is a commune in central France known for its notable modernist architecture, including works by Le Corbusier such as the Maison de la Culture.
-
E.
Vénissieux
Vénissieux is a suburban commune in eastern France that forms part of the urban area of Lyon and is known for its industrial heritage and diverse population.
- 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_69d7bdfa933c8190b5a27aa4a08a19b7 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d97dc8c0848190946e109ec98e4479 |
completed | April 10, 2026, 10:46 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd7a2796cc81908b6d4cf71f39e88a |
completed | May 8, 2026, 5:52 a.m. |
Created at: April 9, 2026, 5:43 p.m.