Triple
T18880126
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marcelo Vieira |
E461803
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Vieira |
—
|
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: Vieira | Statement: [Marcelo Vieira, familyName, Vieira]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Vieira Context triple: [Marcelo Vieira, familyName, Vieira]
-
A.
Vieira
Vieira is a French former professional footballer and World Cup winner who became a prominent defensive midfielder and later a football manager.
-
B.
Vieira
chosen
Vieira is a Portuguese surname commonly associated with people of Lusophone heritage, including notable figures in politics, sports, and the arts.
-
C.
Dos Santos
Dos Santos is a common Portuguese-language surname, especially prevalent in Brazil and other Lusophone countries.
-
D.
Ramos da Costa
Ramos da Costa is a Portuguese-language surname associated with individuals such as Francisco Ramos da Costa.
-
E.
Amarante
Amarante is a Portuguese wine subregion within Vinho Verde, known for producing fresh, often slightly sparkling white wines as well as some reds and rosés.
- 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_69d8dcfc3430819095ee6fc0eb4c06a5 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5c3d133f08190a482e601c1866662 |
completed | April 20, 2026, 6:12 a.m. |
Created at: April 10, 2026, 11:57 a.m.