Triple

T20053693
Position Surface form Disambiguated ID Type / Status
Subject Mónica Gaztambide E499269 entity
Predicate portrayedBy P1507 FINISHED
Object Esther Acebo 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: Esther Acebo | Statement: [Mónica Gaztambide, portrayedBy, Esther Acebo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Esther Acebo
Context triple: [Mónica Gaztambide, portrayedBy, Esther Acebo]
  • A. Esther Acebo chosen
    Esther Acebo is a Spanish actress and television presenter best known internationally for her role as Mónica Gaztambide (Stockholm) in the hit series "Money Heist."
  • B. Esther García
    Esther García is a prominent Spanish film producer best known for her long-standing collaboration with director Pedro Almodóvar on acclaimed films such as "Volver."
  • C. Esther Fernández
    Esther Fernández was a prominent Mexican film actress known for her work during the Golden Age of Mexican cinema.
  • D. María Cortés
    María Cortés was a daughter of the Spanish conquistador Hernán Cortés, belonging to the colonial-era lineage that emerged from his conquests in the Americas.
  • E. Margarita Sanz
    Margarita Sanz is a Mexican actress known for her acclaimed performances in film, television, and theater, often portraying complex, emotionally rich characters.
  • 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_69da6276bcf48190aabbf279192a5fb4 completed April 11, 2026, 3:02 p.m.
NER Named-entity recognition batch_69e66331c7488190840d43792ff09977 completed April 20, 2026, 5:32 p.m.
Created at: April 11, 2026, 3:38 p.m.