Triple
T11942648
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | FIESP Cultural Center |
E284214
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Bela Vista, São Paulo |
E282969
|
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: Bela Vista, São Paulo | Statement: [FIESP Cultural Center, locatedIn, Bela Vista, São Paulo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bela Vista, São Paulo Context triple: [FIESP Cultural Center, locatedIn, Bela Vista, São Paulo]
-
A.
Bela Vista, São Paulo
chosen
Bela Vista is a central neighborhood in São Paulo, Brazil, known for its Italian heritage, vibrant cultural life, and important landmarks such as major theaters and museums.
-
B.
Itaquera, São Paulo
Itaquera, São Paulo is an eastern district of São Paulo best known for hosting Corinthians’ modern football stadium, a key venue from the 2014 FIFA World Cup.
-
C.
Butantã, São Paulo
Butantã is a district in western São Paulo best known for hosting the main campus of the University of São Paulo and several major research and cultural institutions.
-
D.
Osasco
Osasco is a major industrial and commercial city in the metropolitan region of São Paulo, Brazil.
-
E.
Guarulhos
Guarulhos is a major city in the São Paulo metropolitan area of Brazil, known as an important industrial and logistics hub.
- 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_69d6ab2db38c8190b1f0ed6663ef8ada |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d90342bb908190a019ac91a2b82f3d |
completed | April 10, 2026, 2:03 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f63edbcd288190b491a16f2bf8fc62 |
completed | May 2, 2026, 6:13 p.m. |
Created at: April 8, 2026, 9:45 p.m.