Triple
T348074
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cabernet Franc |
E6983
|
entity |
| Predicate | majorRegion |
P285
|
FINISHED |
| Object | Loire Valley |
E49035
|
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: Loire Valley | Statement: [Cabernet Franc, majorRegion, Loire Valley]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Loire Valley Context triple: [Cabernet Franc, majorRegion, Loire Valley]
-
A.
Touraine
Touraine is a historic region in central France, famed for its Loire Valley châteaux, wine production, and role as a former royal heartland.
-
B.
Val-d'Oise
Val-d'Oise is a department in northern France that forms part of the Paris metropolitan region and includes both suburban areas and rural landscapes.
-
C.
Burgundy
Burgundy is a renowned wine-producing region in eastern France, famous for its high-quality Chardonnay and Pinot Noir wines.
-
D.
Côte Chalonnaise
Côte Chalonnaise is a wine-producing subregion of Burgundy in eastern France, known for its value-driven red and white wines primarily from Pinot Noir and Chardonnay.
-
E.
Centre-Val de Loire
chosen
Centre-Val de Loire is a central French region known for its Loire Valley châteaux, historic towns, and extensive agricultural landscapes.
- 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_69a2e7951ba08190960e90823b5078f3 |
completed | Feb. 28, 2026, 1:03 p.m. |
| NER | Named-entity recognition | batch_69a2eb1c1c908190b3a01de893207ed1 |
completed | Feb. 28, 2026, 1:18 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a4176f80488190bbee9a442a6a7076 |
completed | March 1, 2026, 10:39 a.m. |
Created at: Feb. 28, 2026, 1:08 p.m.