Triple

T9438939
Position Surface form Disambiguated ID Type / Status
Subject Safe House E227591 entity
Predicate director P255 FINISHED
Object Daniel Espinosa E227591 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: Daniel Espinosa | Statement: [Safe House, director, Daniel Espinosa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Daniel Espinosa
Context triple: [Safe House, director, Daniel Espinosa]
  • A. Daniel Espinosa chosen
    Daniel Espinosa is a Swedish film director known for action and thriller films such as "Safe House" and "Life."
  • B. Rodrigo Prieto
    Rodrigo Prieto is a renowned Mexican cinematographer known for his visually distinctive work on major films by directors such as Martin Scorsese and Alejandro G. Iñárritu.
  • C. Miguel Ordóñez
    Miguel Ordóñez is an illustrator known for his playful, minimalist artwork in children’s books and other visual storytelling projects.
  • D. Luis Krahl
    Luis Krahl is a mountaineer known for making the first recorded ascent of Cerro San Valentín, the highest peak in Chilean Patagonia.
  • E. David Ortega
    David Ortega is an American architect and politician who serves as the mayor of Scottsdale, Arizona.
  • 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_69ca843884488190ad6cbe0153088234 completed March 30, 2026, 2:10 p.m.
NER Named-entity recognition batch_69cd7ee1c8c48190a2ae8673eee07e9a completed April 1, 2026, 8:24 p.m.
NED1 Entity disambiguation (via context triple) batch_69d1105909248190b3e02a1aa5f06b11 completed April 4, 2026, 1:21 p.m.
Created at: March 30, 2026, 7:50 p.m.