Triple

T16735395
Position Surface form Disambiguated ID Type / Status
Subject Craveiro Lopes E406703 entity
Predicate precededBy P97 FINISHED
Object Óscar Carmona 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: Óscar Carmona | Statement: [Craveiro Lopes, precededBy, Óscar Carmona]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Óscar Carmona
Context triple: [Craveiro Lopes, precededBy, Óscar Carmona]
  • A. Óscar Carmona chosen
    Óscar Carmona was a Portuguese military officer and politician who served as President of Portugal during the early decades of the Estado Novo authoritarian regime.
  • B. Antonio Reynoso
    Antonio Reynoso is an American politician and community advocate who serves as the Borough President of Brooklyn, New York City.
  • C. Carmelo Gómez
    Carmelo Gómez is a Spanish film and theater actor known for his intense performances in acclaimed 1990s Spanish cinema, including collaborations with director Julio Medem.
  • D. Carlos Molina
    Carlos Molina is a personal name shared by multiple notable individuals, including professional athletes and artists from Spanish-speaking countries.
  • E. Eduard Fernández
    Eduard Fernández is a Spanish actor known for his intense and versatile performances in film, television, and theater.
  • 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_69d8838ffb088190a0b11149929006bf completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e39c39c570819088723d59242c5c5c completed April 18, 2026, 2:59 p.m.
Created at: April 10, 2026, 5:20 a.m.