Triple

T23101386
Position Surface form Disambiguated ID Type / Status
Subject Love and Other Catastrophes E576038 entity
Predicate distributor P1951 FINISHED
Object Beyond Films 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: Beyond Films | Statement: [Love and Other Catastrophes, distributor, Beyond Films]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Beyond Films
Context triple: [Love and Other Catastrophes, distributor, Beyond Films]
  • A. Beyond Films chosen
    Beyond Films is an Australian film distribution and production company known for handling a range of independent and international titles.
  • B. Bay Films
    Bay Films is a film production company founded by director Michael Bay, known for producing high-octane action movies and large-scale Hollywood blockbusters.
  • C. Bold Films
    Bold Films is an independent American film production and financing company known for backing distinctive genre and auteur-driven movies such as "Nightcrawler" and "Whiplash."
  • D. Echo Films
    Echo Films is a film and television production company co-founded by Jennifer Aniston, known for producing character-driven projects including the series "The Morning Show."
  • E. Brio Films
    Brio Films is a French film production company known for producing imaginative and visually distinctive movies such as Michel Gondry’s "Mood Indigo."
  • 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_69e245c060b48190a9bd61a47a16db17 completed April 17, 2026, 2:37 p.m.
NER Named-entity recognition batch_69f18de8c5b4819095cddf989cade60d completed April 29, 2026, 4:49 a.m.
Created at: April 17, 2026, 3:58 p.m.