Triple

T16093042
Position Surface form Disambiguated ID Type / Status
Subject Pedro Vaz E390405 entity
Predicate hasName P744 FINISHED
Object Pedro Vaz E390405 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: Pedro Vaz | Statement: [Pedro Vaz, hasName, Pedro Vaz]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Pedro Vaz
Context triple: [Pedro Vaz, hasName, Pedro Vaz]
  • A. Pedro Vaz chosen
    Pedro Vaz is a small village located on the island of Maio in Cape Verde.
  • B. Antão Vaz
    Antão Vaz is a Portuguese white wine grape variety, particularly associated with the Alentejo region, known for producing aromatic, full-bodied wines with good acidity and aging potential.
  • C. Afonso de Paiva
    Afonso de Paiva was a 15th-century Portuguese explorer and diplomat known for his overland expedition to Ethiopia and the Red Sea region in search of Prester John and new trade routes.
  • D. Pedro de Castro
    Pedro de Castro was a Spanish architect known for designing prominent public buildings in Puerto Rico, including the island’s Capitol.
  • E. Pedro da Fonseca
    Pedro da Fonseca was a 16th-century Portuguese Jesuit philosopher and theologian, often called the "Portuguese Aristotle" for his influential work in logic and metaphysics within the scholastic tradition.
  • 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_69d87f198bc48190a8b7e53ca15b7ead completed April 10, 2026, 4:39 a.m.
NER Named-entity recognition batch_69e1858ed09881909bde122971d95753 completed April 17, 2026, 12:57 a.m.
NED1 Entity disambiguation (via context triple) batch_69ffeb973c88819091fe284420088e7e completed May 10, 2026, 2:21 a.m.
Created at: April 10, 2026, 4:59 a.m.