Triple
T18999195
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vendômois |
E464898
|
entity |
| Predicate | hasVariant |
P455
|
FINISHED |
| Object | Vendômoise |
—
|
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: Vendômoise | Statement: [Vendômois, hasVariant, Vendômoise]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Vendômoise Context triple: [Vendômois, hasVariant, Vendômoise]
-
A.
Vendômois
chosen
Vendômois is the French demonym referring to inhabitants or natives of the town of Vendôme in central France.
-
B.
Perche Vendômois
Perche Vendômois is a rural historical and natural region in central France known for its rolling landscapes, small villages, and cultural heritage within the Loir-et-Cher department.
-
C.
Saintois
A Saintois is a resident or native of the coastal commune of Saintes-Maries-de-la-Mer in southern France.
-
D.
Bresse
Bresse is a historical region in eastern France known for its rich agricultural land, distinctive culinary traditions, and cultural ties to the Franco-Provençal linguistic area.
-
E.
Auberjonois
Auberjonois is a surname most prominently associated with René Auberjonois, an American actor known for roles in film, television, and voice work.
- 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_69d8dd01a56c81909694a128c66b21d7 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5d684d37c8190b975f04a47fa7b92 |
completed | April 20, 2026, 7:32 a.m. |
Created at: April 10, 2026, 12:01 p.m.