Triple
T36411716
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chianti region |
E896896
|
entity |
| Predicate | regulatesWineUnder |
P41067
|
FINISHED |
| Object | Chianti DOCG |
—
|
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: Chianti DOCG | Statement: [Chianti region, regulatesWineUnder, Chianti DOCG]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: regulatesWineUnder Context triple: [Chianti region, regulatesWineUnder, Chianti DOCG]
-
A.
regulatesWineType
Indicates that one entity has authority or influence over the rules, standards, or conditions governing a particular type of wine.
-
B.
wineRegulationBody
chosen
Indicates that a regulatory organization has authority over the production, labeling, or distribution standards for a particular wine or wine-producing region.
-
C.
wineRegulationStatus
Indicates the regulatory classification or compliance status that applies to a given wine under relevant laws or standards.
-
D.
regulatesAlcoholLevel
Indicates a relationship where one entity controls, adjusts, or maintains the alcohol level of another entity or system.
-
E.
wineLaw
Indicates a legal or regulatory relationship governing the production, sale, labeling, or distribution of wine.
- 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_69f76e54ce408190849acc3f7758937c |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69fddac4e2f48190a9301d3422658b29 |
completed | May 8, 2026, 12:44 p.m. |
| PD | Predicate disambiguation | batch_69fdda06969c8190b5d033964ea2a690 |
completed | May 8, 2026, 12:41 p.m. |
Created at: May 3, 2026, 4:10 p.m.