Triple

T2200432
Position Surface form Disambiguated ID Type / Status
Subject Monster E50475 entity
Predicate cinematographyBy P1953 FINISHED
Object Steven Bernstein E237361 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: Steven Bernstein | Statement: [Monster, cinematographyBy, Steven Bernstein]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Steven Bernstein
Context triple: [Monster, cinematographyBy, Steven Bernstein]
  • A. Steven Bernstein chosen
    Steven Bernstein is a cinematographer and film director known for his work on feature films such as the comedy "White Chicks."
  • B. Scott Bernstein
    Scott Bernstein is a film producer known for working on major Hollywood projects, including the Aretha Franklin biopic "Respect" (2021).
  • C. Jamie Bernstein
    Jamie Bernstein is an American narrator, writer, and filmmaker best known for her work promoting and interpreting the legacy of her father, composer and conductor Leonard Bernstein.
  • D. Alexander Bernstein
    Alexander Bernstein is an American educator and arts advocate, best known as the son of renowned composer and conductor Leonard Bernstein.
  • E. Jacob Bernstein
    Jacob Bernstein is an American journalist, writer, and filmmaker known for his work with The New York Times and his documentaries on cultural and media figures.
  • 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_69a88b044ab48190add007487680f009 completed March 4, 2026, 7:41 p.m.
NER Named-entity recognition batch_69abbfa06bb4819092d7021358846e5f completed March 7, 2026, 6:03 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae5dbb6e8481908610337cfd2a4bd1 completed March 9, 2026, 5:42 a.m.
Created at: March 4, 2026, 7:46 p.m.