Triple
T11784511
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bugey |
E280236
|
entity |
| Predicate | grapeVarieties |
P33546
|
FINISHED |
| Object | Gamay |
E45511
|
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: Gamay | Statement: [Bugey, grapeVarieties, Gamay]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gamay Context triple: [Bugey, grapeVarieties, Gamay]
-
A.
Gamay
chosen
Gamay is a red wine grape variety best known for producing light, fruity wines, particularly in France’s Beaujolais region.
-
B.
Gamay
Gamay is a coastal municipality in the province of Northern Samar in the Philippines, known for its rural communities and fishing- and agriculture-based local economy.
-
C.
Gaume
Gaume is a culturally distinct region in southern Belgium known for its milder microclimate, French-speaking population, and characteristic rural landscapes.
-
D.
Marlais
Marlais is the distinctive middle name of Welsh poet and writer Dylan Thomas, reflecting his Welsh heritage.
-
E.
Valleiry
Valleiry is a small French commune in the Haute-Savoie department of the Auvergne-Rhône-Alpes region in southeastern France, near the Swiss border.
- 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_69d6ab258b808190b1735835c841e3a4 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d8a585795c8190aa8a5edf0d99b47f |
completed | April 10, 2026, 7:23 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f130e5a21881909b59e39cd96ec676 |
completed | April 28, 2026, 10:12 p.m. |
Created at: April 8, 2026, 9:42 p.m.