Triple
T11398107
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | USP |
E270032
|
entity |
| Predicate | hasCampusIn |
P4623
|
FINISHED |
| Object | Pirassununga |
E270036
|
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: Pirassununga | Statement: [USP, hasCampusIn, Pirassununga]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Pirassununga Context triple: [USP, hasCampusIn, Pirassununga]
-
A.
Pirassununga
chosen
Pirassununga is a municipality in the state of São Paulo, Brazil, known for its agricultural activities and as a site of a major University of São Paulo campus.
-
B.
Coruripe
Coruripe is a coastal municipality in northeastern Brazil known for its beaches, fishing activities, and sugarcane agriculture.
-
C.
Panarima
Panarima is a musical track featured on the album "Legend of the Sun Virgin."
-
D.
Sapucaia
Sapucaia is a municipality located in the mountainous Região Serrana of the state of Rio de Janeiro, Brazil.
-
E.
Parangolé
Parangolé is a series of wearable, participatory artworks by Brazilian artist Hélio Oiticica that merge sculpture, performance, and viewer interaction to challenge traditional notions of art and spectatorship.
- 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_69d6aacdbc6c8190af6dc3d5f5d22836 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d80019d3d48190a2f473deb6eae33a |
completed | April 9, 2026, 7:38 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e58cd74280819092f8c420630f4889 |
completed | April 20, 2026, 2:17 a.m. |
Created at: April 8, 2026, 9:34 p.m.