Triple
T5262125
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Champenois |
E118849
|
entity |
| Predicate | hasDialectContinuumWith |
P18451
|
FINISHED |
| Object | Lorrain |
E118850
|
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: Lorrain | Statement: [Champenois, hasDialectContinuumWith, Lorrain]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lorrain Context triple: [Champenois, hasDialectContinuumWith, Lorrain]
-
A.
Lorrain
chosen
Lorrain is a Romance regional language spoken in parts of eastern France and neighboring areas of Belgium, including the Walloon region.
-
B.
Prunelart
Prunelart is a rare, traditional red wine grape variety from southwest France, historically associated with the Gaillac region and valued for producing deeply colored, robust wines.
-
C.
Montesson
Montesson is a suburban commune in the Yvelines department of north-central France, located to the northwest of Paris along the Seine River.
-
D.
Drouet
Drouet is a French surname most notably associated with Jean-Baptiste Drouet, the postmaster who helped identify and arrest King Louis XVI during his attempted flight in 1791.
-
E.
Hautepierre
Hautepierre is a residential district in the western part of Strasbourg, France, known for its large housing estates and local commercial centers.
- 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_69bd446a42c88190b7ecbef006561d55 |
completed | March 20, 2026, 12:58 p.m. |
| NER | Named-entity recognition | batch_69bd7bd0c5f48190a1be89314c59f96b |
completed | March 20, 2026, 4:54 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69befe85a3f88190ae014b18b1df202e |
completed | March 21, 2026, 8:24 p.m. |
Created at: March 20, 2026, 1:50 p.m.