Triple

T7790957
Position Surface form Disambiguated ID Type / Status
Subject Maio E180176 entity
Predicate hasSettlement P1068 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: [Maio, hasSettlement, Pedro Vaz]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Pedro Vaz
Context triple: [Maio, hasSettlement, Pedro Vaz]
  • A. Pedro Vaz chosen
    Pedro Vaz is a small village located on the island of Maio in Cape Verde.
  • B. 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.
  • C. Pedro de Castro
    Pedro de Castro was a Spanish architect known for designing prominent public buildings in Puerto Rico, including the island’s Capitol.
  • D. Henrique Lopes de Mendonça
    Henrique Lopes de Mendonça was a Portuguese playwright, poet, and naval officer best known for writing the lyrics to Portugal’s national anthem, “A Portuguesa.”
  • E. Matias de Albuquerque
    Matias de Albuquerque was a Portuguese colonial military leader best known for organizing and leading the defense of northeastern Brazil against Dutch invasions in the early 17th century.
  • 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_69ca827d22208190b4dc5aa680edcf5d completed March 30, 2026, 2:02 p.m.
NER Named-entity recognition batch_69cae9375dcc8190a6cb696c02aeceb7 completed March 30, 2026, 9:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69cb13b38e708190a688ce4effbf7c48 completed March 31, 2026, 12:22 a.m.
Created at: March 30, 2026, 4:30 p.m.