Triple

T22002746
Position Surface form Disambiguated ID Type / Status
Subject How to Kill Your Neighbor's Dog (2000 film) E543371 entity
Predicate director P255 FINISHED
Object Michael Kalesniko 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: Michael Kalesniko | Statement: [How to Kill Your Neighbor's Dog (2000 film), director, Michael Kalesniko]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Michael Kalesniko
Context triple: [How to Kill Your Neighbor's Dog (2000 film), director, Michael Kalesniko]
  • A. Michael Kalesniko chosen
    Michael Kalesniko is a Canadian screenwriter and film director known for his darkly comedic and character-driven work in independent cinema.
  • B. Calvin Wimmer
    Calvin Wimmer is a film editor best known for his work on the science fiction horror movie "The Cloverfield Paradox."
  • C. Sean Jablonski
    Sean Jablonski is an American television writer and producer known for his work on drama series such as Project Blue Book and Satisfaction.
  • D. Aaron Korsh
    Aaron Korsh is an American television writer and producer best known for creating the legal drama series "Suits."
  • E. Mike Kuchar
    Mike Kuchar is an American underground filmmaker and artist known for his campy, low-budget, and highly influential experimental films that helped define New York’s underground cinema scene in the 1960s.
  • 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_69e11e2c814c8190837d072789000486 completed April 16, 2026, 5:36 p.m.
NER Named-entity recognition batch_69f1276bf2a48190910d9c27f1c5e74f completed April 28, 2026, 9:32 p.m.
Created at: April 16, 2026, 8:20 p.m.