Triple

T20359028
Position Surface form Disambiguated ID Type / Status
Subject The Pier E496725 entity
Predicate mainCharacter P1183 FINISHED
Object Verónica 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: Verónica | Statement: [The Pier, mainCharacter, Verónica]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Verónica
Context triple: [The Pier, mainCharacter, Verónica]
  • A. Verónica chosen
    Verónica is a Spanish horror film produced by Apaches Entertainment, known for its chilling portrayal of a teenager haunted by supernatural forces after using a Ouija board.
  • B. Verónica
    Verónica is the central protagonist of the Spanish thriller-drama series "El embarcadero," whose life becomes entangled in a complex web of love, secrets, and betrayal.
  • C. Veronika
    Veronika is the troubled young protagonist of Paulo Coelho's novel "Veronika Decides to Die," whose suicide attempt leads her to a transformative stay in a mental institution.
  • D. Veronika
    Veronika is the tragic, resilient young woman at the heart of the Soviet World War II film "The Cranes Are Flying," whose life and love are shattered by the war.
  • E. Veronica
    Veronica is the sharp-witted, disillusioned high school protagonist of the dark comedy film "Heathers."
  • 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_69e0b4a3f7f48190b37f354574028ca6 completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e678573fc481908bf257e6ed41d750 completed April 20, 2026, 7:02 p.m.
Created at: April 16, 2026, 11:25 a.m.