Triple

T20080548
Position Surface form Disambiguated ID Type / Status
Subject La embajada E499987 entity
Predicate hasCastMember P2308 FINISHED
Object Chino Darín 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: Chino Darín | Statement: [La embajada, hasCastMember, Chino Darín]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Chino Darín
Context triple: [La embajada, hasCastMember, Chino Darín]
  • A. Chino Darín chosen
    Chino Darín is an Argentine actor known for his work in film and television, and as the son of acclaimed actor Ricardo Darín.
  • B. Miguel Ángel Carbonell
    Miguel Ángel Carbonell is a Spanish legal scholar and constitutional law expert known for his extensive academic work, publications, and public commentary on legal and constitutional issues.
  • C. Del Castro
    Del Castro is a variant form of the surname Castro, typically used as a family name in Spanish- and Portuguese-speaking contexts.
  • D. Diego Luna
    Diego Luna is a Mexican actor, director, and producer best known internationally for his roles in films like "Y Tu Mamá También" and "Rogue One: A Star Wars Story."
  • E. Robert Aramayo
    Robert Aramayo is a British actor known for his roles in film and television, including his breakout performance as young Ned Stark in "Game of Thrones" and prominent parts in series such as "Behind Her Eyes" and "The Lord of the Rings: The Rings of Power."
  • 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_69da627770948190997f486f9a2e370f completed April 11, 2026, 3:02 p.m.
NER Named-entity recognition batch_69e66557c19c8190b511857490bbd423 completed April 20, 2026, 5:41 p.m.
Created at: April 11, 2026, 3:41 p.m.