Triple
T9965765
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dauphin |
E195679
|
entity |
| Predicate | territorialAssociation |
P12445
|
FINISHED |
| Object | Dauphiné |
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: Dauphiné | Statement: [Dauphin, territorialAssociation, Dauphiné]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dauphiné Context triple: [Dauphin, territorialAssociation, 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.
Côte des Bar
Côte des Bar is a southern Champagne-producing area in France known for its rolling hills, Kimmeridgian soils, and Pinot Noir–dominant sparkling wines.
-
C.
La Dôle
La Dôle is a prominent mountain peak in the Jura range of western Switzerland, known for its panoramic views over Lake Geneva and the Alps and for hosting telecommunications and weather facilities near its summit.
-
D.
Aube
Aube is a department in northeastern France known for its historic towns, Champagne vineyards, and rural landscapes.
-
E.
Côteaux
Côteaux is a coastal commune in Haiti’s Sud Department known for its rural character and Caribbean shoreline.
- 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_69ca82ebd1288190912f9e4482d1fa35 |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cdb71c38488190a6f3cda11994f6a2 |
completed | April 2, 2026, 12:23 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d23da2d7988190b8603ddb151996d9 |
completed | April 5, 2026, 10:46 a.m. |
Created at: March 30, 2026, 8:47 p.m.