Triple

T20080532
Position Surface form Disambiguated ID Type / Status
Subject La embajada E499987 entity
Predicate productionCompany P490 FINISHED
Object Bambú Producciones 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: Bambú Producciones | Statement: [La embajada, productionCompany, Bambú Producciones]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bambú Producciones
Context triple: [La embajada, productionCompany, Bambú Producciones]
  • A. Bambú Producciones chosen
    Bambú Producciones is a Spanish television production company known for creating popular series such as "High Seas," "Gran Hotel," and "Velvet."
  • B. Iguana Producciones
    Iguana Producciones is a film and television production company known for producing the acclaimed Mexican horror film "Cronos" directed by Guillermo del Toro.
  • C. Ida y Vuelta Producciones
    Ida y Vuelta Producciones is a Spanish television production company known for creating popular drama series.
  • D. Malpaso Productions
    Malpaso Productions is Clint Eastwood’s film production company, known for producing many of his acclaimed movies across several decades.
  • E. Pol-ka Producciones
    Pol-ka Producciones is a prominent Argentine television and film production company known for creating popular telenovelas, series, and movies.
  • 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.