Triple
T12313249
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | São Paulo State University |
E293534
|
entity |
| Predicate | hasCampusIn |
P4623
|
FINISHED |
| Object | Rio Claro |
E297769
|
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: Rio Claro | Statement: [São Paulo State University, hasCampusIn, Rio Claro]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rio Claro Context triple: [São Paulo State University, hasCampusIn, Rio Claro]
-
A.
Rio Claro
chosen
Rio Claro is a municipality in the interior of Brazil’s state of São Paulo, known for its industrial activity and regional educational institutions.
-
B.
Rio Claro
Rio Claro is a town in southeastern Trinidad known as a commercial and transportation hub for the surrounding rural communities.
-
C.
Conceição
Conceição is a civil parish located on Faial Island in the Azores archipelago of Portugal.
-
D.
Itatiba
Itatiba is a municipality in southeastern Brazil known for its quality of life and proximity to the metropolitan region of Campinas in the state of São Paulo.
-
E.
Rio Branco
Rio Branco is the capital city of the Brazilian state of Acre, located in the western Amazon region.
- 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_69f6a533a2788190b885c000c29f4e87 |
completed | May 3, 2026, 1:30 a.m. |
Created at: April 8, 2026, 9:53 p.m.