Triple

T12524577
Position Surface form Disambiguated ID Type / Status
Subject Fernanda Montenegro E299402 entity
Predicate familyName P18 FINISHED
Object da Silva E873428 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: da Silva | Statement: [Fernanda Montenegro, familyName, da Silva]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: da Silva
Context triple: [Fernanda Montenegro, familyName, da Silva]
  • A. da Silva chosen
    da Silva is a common Portuguese-language surname widely used in Brazil and other Lusophone countries.
  • B. da Silva Ferreira
    Da Silva Ferreira is the Portuguese family name of Eusébio, the legendary Mozambique-born footballer widely regarded as one of the greatest players of all time.
  • C. de Silva
    de Silva is a Spanish noble family name historically associated with prominent aristocratic lineages such as the Dukes of Alba.
  • D. da Silva Costa
    da Silva Costa is a Portuguese-language surname most notably borne by Brazilian civil engineer Heitor da Silva Costa, designer of Rio de Janeiro’s Christ the Redeemer statue.
  • E. da Silva Rocha
    da Silva Rocha is a Portuguese-language family name associated with Brazilian football legend Roberto Carlos.
  • 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_69d6ada5cdd48190860d9ce30aff69be completed April 8, 2026, 7:33 p.m.
NER Named-entity recognition batch_69d9545c2aa081908e8a5a94d30e23eb completed April 10, 2026, 7:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69f64bc159c88190835fea5c0d9ee799 completed May 2, 2026, 7:08 p.m.
Created at: April 8, 2026, 9:57 p.m.