Triple
T12489486
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Metropolitan Region of Campinas |
E298523
|
entity |
| Predicate | hasMunicipality |
P847
|
FINISHED |
| Object | Itatiba |
E302061
|
NE 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: Itatiba | Statement: [Metropolitan Region of Campinas, hasMunicipality, Itatiba]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Itatiba Context triple: [Metropolitan Region of Campinas, hasMunicipality, Itatiba]
-
A.
Itatiba
chosen
Itatiba is a municipality in southeastern Brazil known for its quality of life and proximity to the metropolitan region of Campinas in the state of São Paulo.
-
B.
Itapira
Itapira is a municipality in southeastern Brazil known for its agricultural activities and location within the interior of the state of São Paulo.
-
C.
Itapeva
Itapeva is a municipality in the state of São Paulo, Brazil, known for its regional agricultural economy and educational institutions.
-
D.
Pirapora
Pirapora is a municipality in the state of Minas Gerais, Brazil, known for its location on the São Francisco River and its river-based tourism and commerce.
-
E.
Guararema
Guararema is a Brazilian municipality in the state of São Paulo, known for its preserved historic center, riverside landscapes, and eco-tourism attractions.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d6ada377208190a36011199a4d8558 |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d94de1db9481909ddf70eb81cdb714 |
completed | April 10, 2026, 7:22 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6c0d6947c819080d33199d331724c |
completed | May 3, 2026, 3:28 a.m. |
Created at: April 8, 2026, 9:56 p.m.