Triple
T12294356
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Guarulhos |
E293044
|
entity |
| Predicate | borderedBy |
P224
|
FINISHED |
| Object | Itaquaquecetuba |
E326273
|
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: Itaquaquecetuba | Statement: [Guarulhos, borderedBy, Itaquaquecetuba]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Itaquaquecetuba Context triple: [Guarulhos, borderedBy, Itaquaquecetuba]
-
A.
Itaquaquecetuba
chosen
Itaquaquecetuba is a municipality in the Greater São Paulo metropolitan area of southeastern Brazil, known for its rapid urban growth and industrial activity.
-
B.
Itatiba
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.
-
C.
Itapura
Itapura is a municipality in the state of São Paulo, Brazil, located on the banks of the Tietê River near its confluence with the Paraná River.
-
D.
Itanhaém
Itanhaém is a coastal municipality in southeastern Brazil known for its beaches, historic colonial center, and tourism along the São Paulo state shoreline.
-
E.
Macuco
Macuco is a small municipality located in the mountainous Região Serrana of the state of Rio de Janeiro, Brazil.
- 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_69d6ab690ad081908c0ed3870ec82d53 |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d93ed7251c8190b94d7cd75ad49b9c |
completed | April 10, 2026, 6:17 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f61e79bf548190bf7f314222ed1ed1 |
completed | May 2, 2026, 3:55 p.m. |
Created at: April 8, 2026, 9:52 p.m.