Triple

T22793995
Position Surface form Disambiguated ID Type / Status
Subject Marina Ortiz de Gaete E564190 entity
Predicate givenName P17 FINISHED
Object Marina 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: Marina | Statement: [Marina Ortiz de Gaete, givenName, Marina]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Marina
Context triple: [Marina Ortiz de Gaete, givenName, Marina]
  • A. Marina
    Marina is a recurring comedic character in the long-running British sitcom "Last of the Summer Wine," known for her flirtatious relationship with the married Howard.
  • B. Marina
    Marina is a 2012 Tamil coming-of-age drama film that helped establish Sivakarthikeyan as a leading actor in the Tamil film industry.
  • C. Marina chosen
    Marina is a female given name of Latin origin, commonly used in various cultures and often associated with the sea.
  • D. Marina
    Marina is the eccentric, childlike porn actress who becomes the obsessive focus of a recently released psychiatric patient in Pedro Almodóvar’s dark romantic comedy film "Tie Me Up! Tie Me Down!".
  • E. Marina
    Marina is a supporting character in Anton Chekhov’s play "Uncle Vanya," contributing to the domestic and emotional atmosphere of the story.
  • 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_69e2458185f88190b0045227ee420411 completed April 17, 2026, 2:36 p.m.
NER Named-entity recognition batch_69f17cd81794819091b528600e322d7b completed April 29, 2026, 3:36 a.m.
Created at: April 17, 2026, 3:30 p.m.