Triple
T3991330
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vivaro-Alpine |
E86995
|
entity |
| Predicate | hasDialect |
P4251
|
FINISHED |
| Object | Dauphinois |
E220592
|
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: Dauphinois | Statement: [Vivaro-Alpine, hasDialect, Dauphinois]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dauphinois Context triple: [Vivaro-Alpine, hasDialect, Dauphinois]
-
A.
Auberjonois
Auberjonois is a surname most prominently associated with René Auberjonois, an American actor known for roles in film, television, and voice work.
-
B.
Moulinois
Moulinois is the French term for an inhabitant or native of the town of Moulins in central France.
-
C.
Brionnais
Brionnais is a historic rural region in eastern France known for its Romanesque churches, traditional stone villages, and Charolais cattle farming.
-
D.
Puget-Théniers
Puget-Théniers is a small commune in southeastern France known for its picturesque setting in the Var valley and its historic Provençal village character.
-
E.
Dauphiné
chosen
Dauphiné is a historical region in southeastern France, centered around Grenoble in the Alps, known for its role in French history and distinctive alpine culture.
- 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_69aed94118148190975e6aa4e554cde9 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefa02ed6881908e31d342413fed26 |
completed | March 9, 2026, 4:49 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b54035e92c81909dc2be18719b062c |
completed | March 14, 2026, 11:02 a.m. |
Created at: March 9, 2026, 3:33 p.m.