Triple
T13343563
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marjorie Estiano |
E317887
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object |
Dias de Oliveira
Dias de Oliveira is the family name of Brazilian actress and singer Marjorie Estiano.
|
E1035593
|
NE FINISHED |
How this triple was built (4 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: Dias de Oliveira | Statement: [Marjorie Estiano, familyName, Dias de Oliveira]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dias de Oliveira Context triple: [Marjorie Estiano, familyName, Dias de Oliveira]
-
A.
Ramos de Azevedo
Ramos de Azevedo was a prominent Brazilian architect and engineer known for shaping São Paulo’s urban landscape in the late 19th and early 20th centuries.
-
B.
Engenho de Dentro
Engenho de Dentro is a neighborhood in Rio de Janeiro, Brazil, known for hosting the Estádio Nilton Santos football stadium.
-
C.
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.
-
D.
Sampaio
Sampaio is a Portuguese surname borne by various notable figures in fields such as politics, sports, and entertainment.
-
E.
Vale dos Sinos
Vale dos Sinos is a populous and industrialized region in the state of Rio Grande do Sul, Brazil, known especially for its footwear and leather industries.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Dias de Oliveira Triple: [Marjorie Estiano, familyName, Dias de Oliveira]
Generated description
Dias de Oliveira is the family name of Brazilian actress and singer Marjorie Estiano.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Dias de Oliveira Target entity description: Dias de Oliveira is the family name of Brazilian actress and singer Marjorie Estiano.
-
A.
Ramos de Azevedo
Ramos de Azevedo was a prominent Brazilian architect and engineer known for shaping São Paulo’s urban landscape in the late 19th and early 20th centuries.
-
B.
Engenho de Dentro
Engenho de Dentro is a neighborhood in Rio de Janeiro, Brazil, known for hosting the Estádio Nilton Santos football stadium.
-
C.
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.
-
D.
Sampaio
Sampaio is a Portuguese surname borne by various notable figures in fields such as politics, sports, and entertainment.
-
E.
Vale dos Sinos
Vale dos Sinos is a populous and industrialized region in the state of Rio Grande do Sul, Brazil, known especially for its footwear and leather industries.
- F. None of above. chosen
Provenance (5 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_69d806b5a3c08190b42c267fb092f98a |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d99e8839b48190b164414b418e756c |
completed | April 11, 2026, 1:06 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f71f417e4081908ab2025a313bfad1 |
completed | May 3, 2026, 10:11 a.m. |
| NEDg | Description generation | batch_69f7204ac36c8190a04e921442489e9c |
completed | May 3, 2026, 10:15 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69f7221887208190ac98945a023bc496 |
completed | May 3, 2026, 10:23 a.m. |
Created at: April 9, 2026, 9:31 p.m.