Triple

T11817090
Position Surface form Disambiguated ID Type / Status
Subject Rachael Horovitz E281027 entity
Predicate employer P7 FINISHED
Object Focus Features E48067 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: Focus Features | Statement: [Rachael Horovitz, employer, Focus Features]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Focus Features
Context triple: [Rachael Horovitz, employer, Focus Features]
  • A. Focus Features chosen
    Focus Features is an American film production and distribution company known for releasing critically acclaimed independent and art-house movies.
  • B. Beyond Films
    Beyond Films is an Australian film distribution and production company known for handling a range of independent and international titles.
  • C. Marché du Film
    Marché du Film is the Cannes Film Festival’s major international film market, where industry professionals buy, sell, and promote films and projects.
  • D. Direct Cinema
    Direct Cinema is a documentary filmmaking movement characterized by unobtrusive, observational techniques that aim to capture reality as it unfolds without scripted narration or interference.
  • E. Greenpoint Films
    Greenpoint Films is a film production company best known for producing the acclaimed period drama "Enchanted April."
  • 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_69d6ab26aae88190b2489efcb2a24234 completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d8a5e760988190b50d13bba5ef5b43 completed April 10, 2026, 7:25 a.m.
NED1 Entity disambiguation (via context triple) batch_69f131b62abc8190a02f584541baaee5 completed April 28, 2026, 10:16 p.m.
Created at: April 8, 2026, 9:42 p.m.