Triple
T21140813
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ivete Sangalo |
E520919
|
entity |
| Predicate | associatedAct |
P37
|
FINISHED |
| Object | Daniela Mercury |
—
|
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: Daniela Mercury | Statement: [Ivete Sangalo, associatedAct, Daniela Mercury]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Daniela Mercury Context triple: [Ivete Sangalo, associatedAct, Daniela Mercury]
-
A.
Daniela Mercury
chosen
Daniela Mercury is a Brazilian singer, songwriter, and performer renowned for her energetic blend of axé, pop, and MPB, and for helping popularize Salvador’s Carnival music worldwide.
-
B.
Nené
Nené is a former Brazilian footballer best known as a prolific forward for S.L. Benfica during the 1970s and 1980s.
-
C.
Madonna Dianora
Madonna Dianora is a character from the German poet Eduard Mörike’s cycle of verse dramas "Lyrische Dramen," featured in one of its poetic plays.
-
D.
Diana Ossana
Diana Ossana is an American screenwriter and producer best known for co-writing the acclaimed film adaptation of "Brokeback Mountain."
-
E.
Durán Madonna
Durán Madonna is a mid-15th-century devotional painting by Early Netherlandish master Rogier van der Weyden, celebrated for its intimate depiction of the Virgin and Child and its refined emotional realism.
- 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_69e0b50b53048190ae34e8abbe3c5ada |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e7235f77708190809d6aa3ee8056aa |
completed | April 21, 2026, 7:12 a.m. |
Created at: April 16, 2026, 2:57 p.m.