Triple

T20221523
Position Surface form Disambiguated ID Type / Status
Subject Andrés de Fonollosa E495265 entity
Predicate portrayedBy P1507 FINISHED
Object Pedro Alonso 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: Pedro Alonso | Statement: [Andrés de Fonollosa, portrayedBy, Pedro Alonso]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Pedro Alonso
Context triple: [Andrés de Fonollosa, portrayedBy, Pedro Alonso]
  • A. Pedro Alonso chosen
    Pedro Alonso is a Spanish actor best known internationally for his role as Berlin in the hit television series "Money Heist" (La Casa de Papel).
  • B. Alfonso Mondelo
    Alfonso Mondelo is a Spanish football manager best known in the United States for his coaching roles in Major League Soccer and his work in player development.
  • C. Pedro del Rey
    Pedro del Rey is a film editor best known for his work on Luis Buñuel’s acclaimed 1961 film "Viridiana."
  • D. Alberto Manrique Martín
    Alberto Manrique Martín was an architect known for his role in designing Colombia’s National Capitol building in Bogotá.
  • E. Antonio Cruz Villalón
    Antonio Cruz Villalón is a Spanish architect best known as a co-founder of the renowned architectural firm Cruz y Ortiz Arquitectos, recognized for its contemporary public and cultural buildings.
  • 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_69da626cff80819097b530718a7c98b6 completed April 11, 2026, 3:02 p.m.
NER Named-entity recognition batch_69e66fd610f881908fdd22b1f8bd2efc completed April 20, 2026, 6:26 p.m.
Created at: April 11, 2026, 11:39 p.m.