Triple
T12294355
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Guarulhos |
E293044
|
entity |
| Predicate | borderedBy |
P224
|
FINISHED |
| Object | Arujá |
E976861
|
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: Arujá | Statement: [Guarulhos, borderedBy, Arujá]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Arujá Context triple: [Guarulhos, borderedBy, Arujá]
-
A.
Arujá
chosen
Arujá is a municipality in the state of São Paulo, Brazil, known for its green areas and residential character within the Greater São Paulo region.
-
B.
Araruama
Araruama is a coastal municipality in the state of Rio de Janeiro, Brazil, known for its large saltwater lagoon and tourism.
-
C.
Araricá
Araricá is a small municipality in the state of Rio Grande do Sul, Brazil, known for its rural character and integration into the Porto Alegre metropolitan region.
-
D.
Vilhena
Vilhena is a municipality in the southern part of the Brazilian state of Rondônia, known as an important regional agricultural and commercial center.
-
E.
Guarapari
Guarapari is a coastal resort city in southeastern Brazil known for its beaches and naturally radioactive monazite sand, which is popularly believed to have therapeutic properties.
- 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_69f6555c73208190a8846a5db1a6802e |
completed | May 2, 2026, 7:49 p.m. |
Created at: April 8, 2026, 9:52 p.m.