Triple

T22022145
Position Surface form Disambiguated ID Type / Status
Subject Boris Pavlikovsky E543870 entity
Predicate influences P9 FINISHED
Object Theo Decker 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: Theo Decker | Statement: [Boris Pavlikovsky, influences, Theo Decker]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Theo Decker
Context triple: [Boris Pavlikovsky, influences, Theo Decker]
  • A. Theo Decker chosen
    Theo Decker is the troubled young protagonist of Donna Tartt’s novel "The Goldfinch," whose life is shaped by a tragic museum bombing and his obsessive attachment to a stolen painting.
  • B. Cliff Bradshaw
    Cliff Bradshaw is the American novelist and central protagonist in the musical "Cabaret," whose relationship with nightclub singer Sally Bowles unfolds against the rise of Nazism in 1930s Berlin.
  • C. Tate Langdon
    Tate Langdon is a troubled, ghostly teenager and central antagonist in the first season of the horror anthology series American Horror Story.
  • D. Elias Pearce
    Elias Pearce was the mountaineer credited with making the first recorded ascent of Mount Shasta in California.
  • E. Lukas Gage
    Lukas Gage is an American actor known for his roles in television series such as "Euphoria," "The White Lotus," and various film and streaming projects.
  • 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_69e11e2e8ea4819084210fe06d3a1b8d completed April 16, 2026, 5:36 p.m.
NER Named-entity recognition batch_69f127c8ac6881909a9e96e0873a3ae2 completed April 28, 2026, 9:34 p.m.
Created at: April 16, 2026, 8:23 p.m.