Triple
T2747697
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Azevêdo |
E60908
|
entity |
| Predicate | hasVariantSpelling |
P457
|
FINISHED |
| Object | Azevedo |
E60908
|
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: Azevedo | Statement: [Azevêdo, hasVariantSpelling, Azevedo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Azevedo Context triple: [Azevêdo, hasVariantSpelling, Azevedo]
-
A.
Cardoso
Cardoso is a common Portuguese-language surname borne by numerous individuals, including prominent Brazilian political and cultural figures.
-
B.
Ribeiro
Ribeiro is a common Portuguese surname borne by numerous individuals across Portugal and the Lusophone world.
-
C.
Jordão
Jordão is a neighborhood of Recife, Brazil, known as a largely residential area on the city’s outskirts.
-
D.
Ferraz de Vasconcelos
Ferraz de Vasconcelos is a municipality in the metropolitan region of São Paulo, Brazil, known for its urban character and integration into the Greater São Paulo area.
-
E.
Azevêdo
chosen
Azevêdo is a Portuguese-language surname commonly found in Brazil and Portugal, associated with several notable public figures.
- 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_69ab4b79846081909096725374d65ce9 |
completed | March 6, 2026, 9:47 p.m. |
| NER | Named-entity recognition | batch_69abdb4ff7b08190b72edb6a2bc5fd19 |
completed | March 7, 2026, 8:01 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69afbbd341a88190ae0f5eb94a6fdc92 |
completed | March 10, 2026, 6:36 a.m. |
Created at: March 6, 2026, 9:56 p.m.