Triple
T2633721
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Municipal Theatre of São Paulo |
E59694
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | São Paulo (state) |
E60066
|
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: São Paulo (state) | Statement: [Municipal Theatre of São Paulo, locatedIn, São Paulo (state)]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: São Paulo (state) Context triple: [Municipal Theatre of São Paulo, locatedIn, São Paulo (state)]
-
A.
São Paulo
São Paulo is Brazil’s largest city and a major global financial, cultural, and industrial center in South America.
-
B.
state of São Paulo
chosen
The state of São Paulo is Brazil’s most populous and economically developed state, centered on its capital city of São Paulo, a major global financial and cultural hub.
-
C.
State of Rio de Janeiro
The State of Rio de Janeiro is a coastal state in southeastern Brazil known for its capital city of Rio de Janeiro, major ports, tourism, and significant cultural and economic influence.
-
D.
Paulista
Paulista is a coastal city in the northeastern Brazilian state of Pernambuco, known for its beaches and proximity to the Recife metropolitan area.
-
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_69ab4ac8596c8190b34997e73d9e991c |
completed | March 6, 2026, 9:44 p.m. |
| NER | Named-entity recognition | batch_69abd8def9bc8190b2e013abffc7b191 |
completed | March 7, 2026, 7:50 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b0310d7dd8819084d77c659b6fb0ed |
completed | March 10, 2026, 2:56 p.m. |
Created at: March 6, 2026, 9:50 p.m.