Triple
T2694323
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Graziella Bündchen |
E58475
|
entity |
| Predicate | relative |
P37
|
FINISHED |
| Object | Vânia Nonnenmacher |
E288482
|
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: Vânia Nonnenmacher | Statement: [Graziella Bündchen, relative, Vânia Nonnenmacher]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Vânia Nonnenmacher Context triple: [Graziella Bündchen, relative, Vânia Nonnenmacher]
-
A.
Vânia Nonnenmacher
chosen
Vânia Nonnenmacher is a Brazilian woman best known as the mother of supermodel Gisele Bündchen.
-
B.
Mariana Teixeira de Carvalho
Mariana Teixeira de Carvalho is a Brazilian lawyer best known as the wife of U2 bassist Adam Clayton.
-
C.
Fernanda Tadeu
Fernanda Tadeu is a Portuguese educator and public figure best known as the wife of former Prime Minister António Costa.
-
D.
Luciana Barroso
Luciana Barroso is an Argentine former bartender and flight attendant best known as the wife of American actor Matt Damon.
-
E.
Vera Lúcia Cabreira
Vera Lúcia Cabreira was the wife of renowned Brazilian architect Oscar Niemeyer.
- 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_69ab4ac269e481909cb317d79e68b75b |
completed | March 6, 2026, 9:44 p.m. |
| NER | Named-entity recognition | batch_69abda10a9bc81908473d02ab9116cef |
completed | March 7, 2026, 7:56 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69afaf6804b48190ac0bfe464da93025 |
completed | March 10, 2026, 5:43 a.m. |
Created at: March 6, 2026, 9:55 p.m.