Triple
T27085498
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Muscat de Beaumes-de-Venise |
E686024
|
entity |
| Predicate | producedInDepartment |
P179325
|
FINISHED |
| Object | Vaucluse |
—
|
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: Vaucluse | Statement: [Muscat de Beaumes-de-Venise, producedInDepartment, Vaucluse]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: producedInDepartment Context triple: [Muscat de Beaumes-de-Venise, producedInDepartment, Vaucluse]
-
A.
grownInDepartment
chosen
Indicates that something has been cultivated, developed, or produced within a specific department.
-
B.
basedInDepartment
Indicates that an entity operates or has its primary affiliation within a specific department.
-
C.
worksInDepartment
Indicates that an entity is employed in and performs their job duties within a particular department.
-
D.
motherDepartment
Indicates that one department is the parent or higher-level organizational unit of another department.
-
E.
laterDepartment
Indicates that one department occurs or is considered after another in a defined ordering or sequence.
- 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_69ef148940ec819097b5c20fbfbf7c81 |
completed | April 27, 2026, 7:47 a.m. |
| NER | Named-entity recognition | batch_69f727afd5d88190ad48735cd1b32787 |
completed | May 3, 2026, 10:47 a.m. |
| PD | Predicate disambiguation | batch_69f72737c42c8190a3f781a5e98868ff |
completed | May 3, 2026, 10:45 a.m. |
Created at: April 27, 2026, 8:37 a.m.