Triple
T17525050
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kingdom of Arles |
E426771
|
entity |
| Predicate | includedRegion |
P285
|
FINISHED |
| Object | Dauphiné |
—
|
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: Dauphiné | Statement: [Kingdom of Arles, includedRegion, Dauphiné]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dauphiné Context triple: [Kingdom of Arles, includedRegion, Dauphiné]
-
A.
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.
-
B.
Dauphiné region
The Dauphiné region is a historical area in southeastern France, centered around Grenoble and the Alps, known for its mountainous landscapes and role as a traditional stage for major cycling events.
-
C.
Côte Mâconnaise
Côte Mâconnaise is a wine-producing area in the southern part of Burgundy, France, known for its Chardonnay-based white wines.
-
D.
Beaujeu
Beaujeu is the pseudonym of Jean Monceau, under which he is known in his professional and public activities.
-
E.
Bessières
Bessières is a French surname most notably borne by Jean-Baptiste Bessières, a Marshal of the Empire under Napoleon.
- 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_69d889de677081909b22d2657b1f0292 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e452d592a081909bf876d606158b2d |
completed | April 19, 2026, 3:58 a.m. |
Created at: April 10, 2026, 5:49 a.m.