Triple
T20014241
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Daniela Mercuri de Almeida |
E494669
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Nobre Vagabundo |
—
|
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: Nobre Vagabundo | Statement: [Daniela Mercuri de Almeida, notableWork, Nobre Vagabundo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nobre Vagabundo Context triple: [Daniela Mercuri de Almeida, notableWork, Nobre Vagabundo]
-
A.
Nobre Vagabundo
chosen
Nobre Vagabundo is a popular Brazilian axé song by singer Daniela Mercury, known for its upbeat rhythm and strong presence in 1990s Brazilian pop music.
-
B.
El Nogal
El Nogal is an upscale neighborhood in Bogotá, Colombia, known for its residential areas, shopping centers, and business activity within the Chapinero locality.
-
C.
El Pescadero
El Pescadero is a small coastal village in Baja California Sur, Mexico, known for its beaches, surfing, and agricultural fields near the Pacific Ocean.
-
D.
Rua dos Cegos
Rua dos Cegos is a historic street located in the central area of Lisbon, Portugal, within the old quarter of São Nicolau.
-
E.
El Caminero
El Caminero is a major southern terminal station of Mexico City’s Metrobús bus rapid transit system.
- 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_69da626bfd288190aa5d65098b6433ae |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e6623a9bd48190a3344a07540170c7 |
completed | April 20, 2026, 5:28 p.m. |
Created at: April 11, 2026, 3:34 p.m.