Triple

T6163230
Position Surface form Disambiguated ID Type / Status
Subject Daniel Noboa E137493 entity
Predicate name P16 FINISHED
Object Daniel Noboa E137493 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: Daniel Noboa | Statement: [Daniel Noboa, name, Daniel Noboa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Daniel Noboa
Context triple: [Daniel Noboa, name, Daniel Noboa]
  • A. Daniel Noboa chosen
    Daniel Noboa is an Ecuadorian politician and businessman who became one of the country's youngest presidents after winning the 2023 election.
  • B. de Cevallos
    de Cevallos is a Spanish surname historically associated with notable figures in Spain and its former colonies.
  • C. Miguel Esquivel
    Miguel Esquivel is a person notable enough to be recognized as a namesake of the surname Esquivel.
  • D. Juan Pablo Duarte
    Juan Pablo Duarte was a 19th-century Dominican political leader and founding father who played a central role in the Dominican Republic’s independence from Haitian rule.
  • E. Jorge M. Pérez
    Jorge M. Pérez is a prominent Miami-based real estate developer, billionaire, and philanthropist known for his major contributions to the arts and urban development.
  • 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_69c008a54fc88190b6ce4416490ca79d completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c05d5e8edc8190a7a394ee832bac9f completed March 22, 2026, 9:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69c14199f024819089af02b1c0eebfad completed March 23, 2026, 1:35 p.m.
Created at: March 22, 2026, 4:17 p.m.