Triple
T18568033
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Deco |
E453805
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | de Souza |
—
|
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: de Souza | Statement: [Deco, familyName, de Souza]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: de Souza Context triple: [Deco, familyName, de Souza]
-
A.
de Souza
chosen
de Souza is a Portuguese-origin surname commonly found in Lusophone countries and their diasporas.
-
B.
de Souza Faria
de Souza Faria is the family name of Brazilian football legend and prolific striker Romário.
-
C.
de Oliveira
de Oliveira is a Portuguese-language surname commonly found in Brazil and other Lusophone countries, often associated with people of Portuguese or Brazilian heritage.
-
D.
de Medeiros
de Medeiros is the surname of Portuguese actress and filmmaker Maria de Medeiros, known for her work in European cinema and international films.
-
E.
da Silva
da Silva is a common Portuguese-language surname widely used in Brazil and other Lusophone countries.
- 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_69d8d38974308190a9174430ef256b73 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e53affc3e08190b4d16b5ccb0bddbc |
completed | April 19, 2026, 8:28 p.m. |
Created at: April 10, 2026, 11:43 a.m.