Triple
T5978020
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Athos Bulcão |
E133046
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Athos Bulcão |
E152835
|
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: Athos Bulcão | Statement: [Athos Bulcão, name, Athos Bulcão]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Athos Bulcão Context triple: [Athos Bulcão, name, Athos Bulcão]
-
A.
Athos Bulcão
chosen
Athos Bulcão was a Brazilian artist renowned for his modernist tile panels and public art that became iconic elements of Brasília’s architectural landscape.
-
B.
Sebastião
Sebastião is the Portuguese variant of the given name Sebastian, commonly used in Portuguese-speaking countries.
-
C.
Damião
Damião is a Portuguese given name, equivalent to Damian, commonly used in Lusophone countries.
-
D.
Gonçalo
Gonçalo is a Portuguese given name, equivalent to the Spanish name Gonzalo and commonly used for males in Portuguese-speaking countries.
-
E.
Manuel Gomes Archer
Manuel Gomes Archer was a key Brazilian environmentalist and forestry engineer known for leading major reforestation efforts in Rio de Janeiro’s Tijuca National Park.
- 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_69c0086f45e8819098f73dd16d45ec9d |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c04a3e686c81908910c0881ac1624d |
completed | March 22, 2026, 7:59 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c10847cdec81908a4d2d19d8a53d1d |
completed | March 23, 2026, 9:30 a.m. |
Created at: March 22, 2026, 4:04 p.m.