Triple
T8689940
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dão wine region |
E206259
|
entity |
| Predicate | hasAppellationRule |
P84208
|
FINISHED |
| Object | controlled yields |
—
|
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: controlled yields | Statement: [Dão wine region, hasAppellationRule, controlled yields]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAppellationRule Context triple: [Dão wine region, hasAppellationRule, controlled yields]
-
A.
hasAppellationType
Indicates that an entity’s name or title is associated with a specific category or type of appellation.
-
B.
hasAppellation
Indicates that an entity is known, labeled, or referred to by a particular name, title, or designation.
-
C.
hasSubAppellation
Indicates that one appellation (name or title) is a more specific or subordinate form of another appellation.
-
D.
authorizedInAppellation
Indicates that an entity has been officially granted authorization or recognition within a specific appellation or designated geographic area.
-
E.
includesAppellation
Indicates that one entity contains or incorporates another entity’s name, title, or designation as part of its own identification.
- F. None of above. chosen
Provenance (4 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_69ca835481fc819084e33d3bc883bfa6 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc5734602c81909a0687e00f4a4a26 |
completed | March 31, 2026, 11:22 p.m. |
| PD | Predicate disambiguation | batch_69cc4569f9048190b9c86b4c81103d35 |
completed | March 31, 2026, 10:06 p.m. |
| PDg | Predicate description generation | batch_69cc483f06f48190879f4702c8b4ed00 |
completed | March 31, 2026, 10:18 p.m. |
Created at: March 30, 2026, 6:33 p.m.