Triple
T22991166
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aparecida, São Paulo |
E572051
|
entity |
| Predicate | locatedNear |
P294
|
FINISHED |
| Object | Guaratinguetá, São Paulo |
—
|
NE NERFINISHED |
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: Guaratinguetá, São Paulo | Statement: [Aparecida, São Paulo, locatedNear, Guaratinguetá, São Paulo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Guaratinguetá, São Paulo Context triple: [Aparecida, São Paulo, locatedNear, Guaratinguetá, São Paulo]
-
A.
Guaratinguetá
chosen
Guaratinguetá is a historic municipality in southeastern Brazil known for its colonial heritage and religious tourism, located in the state of São Paulo.
-
B.
Guarujá
Guarujá is a coastal resort city in southeastern Brazil known for its popular beaches and tourism.
-
C.
Taquaritinga
Taquaritinga is a municipality in the interior of Brazil’s São Paulo state, known for its agricultural production and regional commerce.
-
D.
Garça
Garça is the Portuguese term for a heron, a long-legged wading bird commonly found near wetlands and waterways.
-
E.
Andradina
Andradina is a municipality in the state of São Paulo, Brazil, known for its agricultural economy and location in the western part of the state.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e245b535808190adef8a9df3c584db |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f182eefd688190853977421540b2ce |
completed | April 29, 2026, 4:02 a.m. |
Created at: April 17, 2026, 3:50 p.m.