Triple
T32270834
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Curitiba urban master plan |
E824409
|
entity |
| Predicate | appliesScale |
P79560
|
FINISHED |
| Object | metropolitan area of Curitiba |
—
|
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: metropolitan area of Curitiba | Statement: [Curitiba urban master plan, appliesScale, metropolitan area of Curitiba]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: appliesScale Context triple: [Curitiba urban master plan, appliesScale, metropolitan area of Curitiba]
-
A.
scalesBy
Indicates a relationship where one quantity, object, or representation is proportionally enlarged or reduced relative to another by a specific scaling factor.
-
B.
scalesWith
Indicates that a change in one quantity is systematically associated with a proportional or otherwise dependent change in another quantity.
-
C.
coversScale
chosen
Indicates that one entity spans, includes, or applies across the full range or extent of another entity’s scale.
-
D.
hasScale
Indicates that one entity possesses or is characterized by a scale or graduated measurement system related to another entity.
-
E.
associatedScale
Indicates that one entity is linked or connected to a particular scale used to measure, classify, or evaluate it.
- 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_69f3490e73588190915f282edd105772 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69fec5c503808190bde0b1829ea43071 |
completed | May 9, 2026, 5:27 a.m. |
| PD | Predicate disambiguation | batch_69fec535dd6c8190a6ab85201f5a04a9 |
completed | May 9, 2026, 5:25 a.m. |
Created at: May 1, 2026, 12:42 a.m.