Triple
T32855327
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Serra da Canastra |
E840358
|
entity |
| Predicate | cheeseTypeProtected |
P94140
|
FINISHED |
| Object | Queijo Canastra |
—
|
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: Queijo Canastra | Statement: [Serra da Canastra, cheeseTypeProtected, Queijo Canastra]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: cheeseTypeProtected Context triple: [Serra da Canastra, cheeseTypeProtected, Queijo Canastra]
-
A.
cheeseType
Indicates that one entity is a specific type or variety of cheese in relation to another entity.
-
B.
cheeseProtectedDesignation
chosen
Indicates that a cheese has an officially recognized protected designation (such as PDO/PGI), linking it to specific geographic origin and production standards.
-
C.
cheeseSpeciality
Indicates that one entity is known for or specializes in producing or offering a particular type of cheese.
-
D.
cheeseMadeFrom
Indicates that one entity is produced or derived as cheese from another entity (typically a source ingredient such as milk).
-
E.
cheeseRipeningStyle
Indicates the method or process by which a cheese is matured or aged to develop its flavor and texture.
- 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_69f349412c78819084459850e11d29f7 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69f6d16f5cb881908eed141afaaa0b51 |
completed | May 3, 2026, 4:39 a.m. |
| PD | Predicate disambiguation | batch_69f6cfe45554819089cbbd538d992132 |
completed | May 3, 2026, 4:32 a.m. |
Created at: May 1, 2026, 1:17 a.m.