Triple
T8394672
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Queijo Nisa |
E198023
|
entity |
| Predicate | hasProductionArea |
P55610
|
FINISHED |
| Object | municipality of Nisa |
—
|
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: municipality of Nisa | Statement: [Queijo Nisa, hasProductionArea, municipality of Nisa]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasProductionArea Context triple: [Queijo Nisa, hasProductionArea, municipality of Nisa]
-
A.
traditionalProductionArea
chosen
Indicates that something originates from or is associated with a region historically recognized for producing it according to established traditions.
-
B.
hasProduction
Indicates that an entity is associated with, or responsible for, the creation or manufacture of another entity or product.
-
C.
hasPrimaryProductionLocation
Indicates that an entity’s main or principal place where it is produced or manufactured is a specified location.
-
D.
hasIndustrialAreaType
Indicates that an entity’s industrial area is classified as a specific type or category of industrial zone.
-
E.
hasAgriculturalProduction
Indicates that an entity engages in or is characterized by the production of agricultural goods such as crops or livestock.
- 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_69ca82f816bc8190ab321c07d72208c1 |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb8185ef60819085cfa7491d35834a |
completed | March 31, 2026, 8:10 a.m. |
| PD | Predicate disambiguation | batch_69cb70d24b248190a326aa6804f942b5 |
completed | March 31, 2026, 6:59 a.m. |
Created at: March 30, 2026, 6:03 p.m.