Triple
T14498100
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cubatão |
E359555
|
entity |
| Predicate | borderedBy |
P224
|
FINISHED |
| Object | Santo André |
E251826
|
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: Santo André | Statement: [Cubatão, borderedBy, Santo André]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Santo André Context triple: [Cubatão, borderedBy, Santo André]
-
A.
Santo André
chosen
Santo André is a major industrial and residential city in the São Paulo metropolitan region of Brazil.
-
B.
Santo André
Santo André is a civil parish in the municipality of Santiago do Cacém in Portugal, known for its coastal location and proximity to the Sines industrial and port complex.
-
C.
São Bernardo do Campo
São Bernardo do Campo is a major industrial city in Brazil known as a key center of the automotive industry within the São Paulo metropolitan area.
-
D.
São Caetano do Sul
São Caetano do Sul is a highly urbanized and affluent city in the São Paulo metropolitan region of Brazil, known for its high quality of life and strong industrial and service sectors.
-
E.
Mogi das Cruzes
Mogi das Cruzes is a municipality in southeastern Brazil known as part of the Greater São Paulo metropolitan area and recognized for its industrial activity and agricultural production.
- 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_69d8279740308190af9df93a3af8592e |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de9311cc748190880c784f173b7f2b |
completed | April 14, 2026, 7:18 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff36455f788190a63507ecda42b04c |
completed | May 9, 2026, 1:27 p.m. |
Created at: April 10, 2026, 1:21 a.m.