Triple

T15211049
Position Surface form Disambiguated ID Type / Status
Subject Brian Banks E363514 entity
Predicate producer P490 FINISHED
Object Monica Levinson E985345 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: Monica Levinson | Statement: [Brian Banks, producer, Monica Levinson]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Monica Levinson
Context triple: [Brian Banks, producer, Monica Levinson]
  • A. Monica Levinson chosen
    Monica Levinson is an American film and television producer known for her work on high-profile comedies and independent features, including the satirical mockumentary "Borat."
  • B. Elizabeth J. Feinler
    Elizabeth J. Feinler is an American information scientist best known for leading early internet directory and naming services, including managing the first WHOIS and domain name registries.
  • C. Paula Weinstein
    Paula Weinstein was an American film producer and studio executive known for overseeing acclaimed dramas and major Hollywood productions.
  • D. Catherine Marks
    Catherine Marks is an acclaimed Australian record producer and audio engineer known for her work with prominent rock and alternative artists.
  • E. Lynn Perkins
    Lynn Perkins was a screenwriter active during Hollywood’s early sound era, known for crafting stories for action-packed war and adventure films such as *The Fighting Marines*.
  • 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_69d85a0b78bc8190b6e5ad51a2c4cfc5 completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e0076ad4ec81908d36f541fca08d72 completed April 15, 2026, 9:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69fed33f9abc8190bf8166c1fd9fcac6 completed May 9, 2026, 6:25 a.m.
Created at: April 10, 2026, 3:11 a.m.