Triple
T28247003
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Burgundy wine region |
E712194
|
entity |
| Predicate | hasAppellationLevel |
P12903
|
FINISHED |
| Object | regional appellation |
—
|
LITERAL 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: regional appellation | Statement: [Burgundy wine region, hasAppellationLevel, regional appellation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAppellationLevel Context triple: [Burgundy wine region, hasAppellationLevel, regional appellation]
-
A.
hasAppellation
Indicates that an entity is known, labeled, or referred to by a particular name, title, or designation.
-
B.
hasAppellationType
chosen
Indicates that an entity’s name or title is associated with a specific category or type of appellation.
-
C.
hasSubAppellation
Indicates that one appellation (name or title) is a more specific or subordinate form of another appellation.
-
D.
hasAppellationRule
Indicates that there is a rule or standard governing how an entity may be named, labeled, or designated.
-
E.
authorizedInAppellation
Indicates that an entity has been officially granted authorization or recognition within a specific appellation or designated geographic area.
- 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_69efb51fb98881909692421959ec0170 |
completed | April 27, 2026, 7:12 p.m. |
| NER | Named-entity recognition | batch_69f74c70fd248190a9d5543afcb08211 |
completed | May 3, 2026, 1:24 p.m. |
| PD | Predicate disambiguation | batch_69f7478e3b548190a51d5d436e2bb036 |
completed | May 3, 2026, 1:03 p.m. |
Created at: April 27, 2026, 11:02 p.m.