Triple
T23412841
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Schalk Ferreira |
E560124
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Ferreira |
—
|
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: Ferreira | Statement: [Schalk Ferreira, familyName, Ferreira]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ferreira Context triple: [Schalk Ferreira, familyName, Ferreira]
-
A.
Ferreira
chosen
Ferreira is a common Portuguese and Spanish surname borne by numerous notable individuals across sports, arts, and public life.
-
B.
Fernandes
Fernandes is a common Portuguese surname, often patronymic in origin and widely found in Portugal, Brazil, and other Lusophone communities.
-
C.
Ferrera
Ferrera is a Spanish-origin surname most prominently associated with American actress and producer America Ferrera.
-
D.
Figueiredo
Figueiredo is a small locality or village within the municipality of Sertã in central Portugal.
-
E.
Andrade
Andrade is a common Portuguese and Spanish surname borne by numerous notable figures across fields such as sports, politics, and the arts.
- 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_69e2454b3a5881909c64773dc8a5d289 |
completed | April 17, 2026, 2:35 p.m. |
| NER | Named-entity recognition | batch_69f1a5124a54819087a7ae2f8a5b3dc0 |
completed | April 29, 2026, 6:28 a.m. |
Created at: April 17, 2026, 5:39 p.m.