Triple
T3108739
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Esch-sur-Alzette |
E64897
|
entity |
| Predicate | hasTwinTown |
P919
|
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: [Esch-sur-Alzette, hasTwinTown, Villeurbanne]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Villeurbanne Context triple: [Esch-sur-Alzette, hasTwinTown, 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.
Saint-Priest
Saint-Priest is a suburban commune in eastern France that forms part of the metropolitan area of Lyon.
-
C.
Boulogne-Billancourt
Boulogne-Billancourt is a densely populated suburban city just southwest of central Paris, known as a major economic and media hub in the Île-de-France region.
-
D.
Meyzieu
Meyzieu is a suburban commune in eastern France, located near Lyon and known for its residential character and proximity to major transport links.
-
E.
Lyon
Lyon is a major city in east-central France known for its historical and architectural landmarks, gastronomy, and role as a key economic and cultural center.
- 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_69ad857eeaf48190b34ebfdaa7a264cf |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada29eacc88190a19c5ca8e53e3dca |
completed | March 8, 2026, 4:23 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b595d57bcc8190b2a6e28437a32b93 |
completed | March 14, 2026, 5:07 p.m. |
Created at: March 8, 2026, 3:04 p.m.