Triple
T38277351
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gattinara DOCG |
E1021997
|
entity |
| Predicate | formerClassificationType |
P16344
|
FINISHED |
| Object | DOC |
—
|
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: DOC | Statement: [Gattinara DOCG, formerClassificationType, DOC]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: formerClassificationType Context triple: [Gattinara DOCG, formerClassificationType, DOC]
-
A.
formerCategory
Indicates that an entity previously belonged to a given category but no longer does.
-
B.
formerType
chosen
Indicates that one entity previously had a certain type, role, or classification but no longer does.
-
C.
previousClassification
Indicates that one classification precedes another in time or in an ordered sequence of classifications.
-
D.
classificationOf
Indicates that one entity serves as a classification, category, or type under which another entity is grouped or organized.
-
E.
wasFormerlyClassifiedAs
Indicates that an entity previously belonged to a particular class or category but no longer does so.
- 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_69f76df0cddc81908d16c1556ff4097f |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_6a013e23698c81909a32d371b6f158d0 |
completed | May 11, 2026, 2:25 a.m. |
| PD | Predicate disambiguation | batch_6a013db04b108190985897aa6e95b4ec |
completed | May 11, 2026, 2:23 a.m. |
Created at: May 3, 2026, 4:30 p.m.