Triple

T20280462
Position Surface form Disambiguated ID Type / Status
Subject Nat Levine E503126 entity
Predicate employer P7 FINISHED
Object Mascot Pictures 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: Mascot Pictures | Statement: [Nat Levine, employer, Mascot Pictures]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mascot Pictures
Context triple: [Nat Levine, employer, Mascot Pictures]
  • A. Mascot Pictures chosen
    Mascot Pictures was an American film production company active during the 1930s, best known for producing low-budget serials and B-movies in Hollywood.
  • B. Mandate Pictures
    Mandate Pictures is an American film production company known for producing independent and mid-budget feature films, including the fantasy-comedy drama "Stranger Than Fiction."
  • C. Magnolia Pictures
    Magnolia Pictures is an American independent film distribution company known for releasing a wide range of arthouse, documentary, and foreign films.
  • D. Pegasus Pictures
    Pegasus Pictures is an Icelandic film and television production company known for working on international projects such as the survival drama "Arctic" (2018).
  • E. Maven Pictures
    Maven Pictures is an independent film production company known for producing character-driven, socially conscious movies.
  • 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_69e0b4b0e79c8190bd61f22ef1329fa8 completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e6768e9f0881909c8fe8772dafd468 completed April 20, 2026, 6:55 p.m.
Created at: April 16, 2026, 10:38 a.m.