Triple
T22996111
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Guia de Ouro Preto |
E572196
|
entity |
| Predicate | setIn |
P1393
|
FINISHED |
| Object | Ouro Preto |
—
|
NE NERFINISHED |
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: Ouro Preto | Statement: [Guia de Ouro Preto, setIn, Ouro Preto]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ouro Preto Context triple: [Guia de Ouro Preto, setIn, Ouro Preto]
-
A.
Ouro Preto
chosen
Ouro Preto is a historic colonial mining town in southeastern Brazil renowned for its well-preserved baroque architecture and role in the country’s gold rush era.
-
B.
São João del-Rei
São João del-Rei is a historic colonial-era city in southeastern Brazil renowned for its baroque architecture, gold-mining heritage, and well-preserved churches.
-
C.
Vila de Rei
Vila de Rei is a small inland municipality in central Portugal known for its rural landscapes and its location near the country’s geodesic center.
-
D.
Pedra Preta
Pedra Preta is a municipality in the Central Potiguar region of the state of Rio Grande do Norte in northeastern Brazil.
-
E.
Sete Lagoas
Sete Lagoas is a city in the state of Minas Gerais, Brazil, known for its industrial activity and automotive manufacturing sector.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e245b535808190adef8a9df3c584db |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f182f3186c81909e0d5177029a72ae |
completed | April 29, 2026, 4:02 a.m. |
Created at: April 17, 2026, 3:50 p.m.