Triple

T12436800
Position Surface form Disambiguated ID Type / Status
Subject Marrowbone E297163 entity
Predicate producer P490 FINISHED
Object Belén Atienza E431587 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: Belén Atienza | Statement: [Marrowbone, producer, Belén Atienza]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Belén Atienza
Context triple: [Marrowbone, producer, Belén Atienza]
  • A. Belén Atienza chosen
    Belén Atienza is a Spanish film producer known for her work on acclaimed international films such as "The Impossible" and collaborations with director J.A. Bayona.
  • B. Belén Rueda
    Belén Rueda is a Spanish actress best known internationally for her leading roles in acclaimed horror and thriller films such as "The Orphanage" and "The Sea Inside."
  • C. Luz Corral
    Luz Corral was the wife of Mexican revolutionary leader Pancho Villa and later became known for preserving and promoting his historical legacy.
  • D. Ángela Jeria
    Ángela Jeria was a Chilean archaeologist and human rights advocate best known as the mother of former Chilean president Michelle Bachelet.
  • E. Pilar Roldán
    Pilar Roldán is a Mexican fencer best known for taking the Olympic Oath for athletes and winning a silver medal in women's foil at the 1968 Mexico City Games.
  • 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_69d6ada166c48190b902972cd2408fa3 completed April 8, 2026, 7:33 p.m.
NER Named-entity recognition batch_69d94d8c8fd481909b35ac504127a1b6 completed April 10, 2026, 7:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6fef6c34481909e18bce1154e7146 completed May 3, 2026, 7:53 a.m.
Created at: April 8, 2026, 9:55 p.m.