Triple
T12313258
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | São Paulo State University |
E293534
|
entity |
| Predicate | hasCampusIn |
P4623
|
FINISHED |
| Object | Ourinhos |
E294683
|
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: Ourinhos | Statement: [São Paulo State University, hasCampusIn, Ourinhos]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ourinhos Context triple: [São Paulo State University, hasCampusIn, Ourinhos]
-
A.
Ourinhos
chosen
Ourinhos is a municipality in the southwestern part of the state of São Paulo, Brazil, known as a regional commercial and agricultural center.
-
B.
Caieiras
Caieiras is a municipality in the metropolitan region of São Paulo, Brazil, known for its industrial activity and surrounding green areas.
-
C.
Arujá
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.
-
D.
Araruama
Araruama is a coastal municipality in the state of Rio de Janeiro, Brazil, known for its large saltwater lagoon and tourism.
-
E.
Afogados
Afogados is a populous neighborhood in the Brazilian city of Recife, known for its busy commercial areas and dense urban character.
- 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_69d6ab6a2b50819082f6aedd32ed608a |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d93f03d3c88190baedffb83465bff8 |
completed | April 10, 2026, 6:18 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f63eefad508190be266c776525a7cc |
completed | May 2, 2026, 6:14 p.m. |
Created at: April 8, 2026, 9:53 p.m.