Triple
T26775009
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Couchey |
E670093
|
entity |
| Predicate | wineClassificationArea |
P97874
|
FINISHED |
| Object | Marsannay AOC |
—
|
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: Marsannay AOC | Statement: [Couchey, wineClassificationArea, Marsannay AOC]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: wineClassificationArea Context triple: [Couchey, wineClassificationArea, Marsannay AOC]
-
A.
wineClassificationRegion
Indicates that a wine is classified according to the geographic region where it is produced or designated.
-
B.
wineRegionCategory
chosen
Indicates a classification relationship where a wine region is assigned to a specific category or type of wine-producing area.
-
C.
wineRegion
Indicates the geographical region or area where a particular wine is produced or originates.
-
D.
wineLawRegionType
Indicates the type or category of legal designation that governs wine production in a particular region.
-
E.
wineLawRegionName
Indicates that a specific name refers to the legal wine-producing region defined by wine regulations.
- F. None of above.
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_69eeb31c925881909b597f6e40056d28 |
completed | April 27, 2026, 12:51 a.m. |
| NER | Named-entity recognition | batch_69f6193170a88190adbbb22150475bb5 |
completed | May 2, 2026, 3:33 p.m. |
| PD | Predicate disambiguation | batch_69f611ad2eb48190ac1ed0090f13f7a9 |
completed | May 2, 2026, 3:01 p.m. |
Created at: April 27, 2026, 4:04 a.m.