Triple
T32855325
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Serra da Canastra |
E840358
|
entity |
| Predicate | cheeseRegion |
P175182
|
FINISHED |
| Object | Canastra cheese production area |
—
|
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: Canastra cheese production area | Statement: [Serra da Canastra, cheeseRegion, Canastra cheese production area]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: cheeseRegion Context triple: [Serra da Canastra, cheeseRegion, Canastra cheese production area]
-
A.
cheeseSpeciality
Indicates that one entity is known for or specializes in producing or offering a particular type of cheese.
-
B.
cheeseProtectedDesignation
Indicates that a cheese has an officially recognized protected designation (such as PDO/PGI), linking it to specific geographic origin and production standards.
-
C.
cheeseType
Indicates that one entity is a specific type or variety of cheese in relation to another entity.
-
D.
typicalCheesePlacement
Indicates the usual or most common spatial position or arrangement of cheese relative to other items or in a given context.
-
E.
cheeseMadeFrom
Indicates that one entity is produced or derived as cheese from another entity (typically a source ingredient such as milk).
- 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_69f349412c78819084459850e11d29f7 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69f6cee547108190ad3bc84297d8f516 |
completed | May 3, 2026, 4:28 a.m. |
| PD | Predicate disambiguation | batch_69f6cc1667a48190b42684f6ec22dae9 |
completed | May 3, 2026, 4:16 a.m. |
| PDg | Predicate description generation | batch_69f6ce6c76bc8190b865343d3f5810c9 |
completed | May 3, 2026, 4:26 a.m. |
Created at: May 1, 2026, 1:17 a.m.