Triple

T16635983
Position Surface form Disambiguated ID Type / Status
Subject A Serious Man E404205 entity
Predicate productionCompany P490 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: [A Serious Man, productionCompany, Focus Features]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Focus Features
Context triple: [A Serious Man, productionCompany, 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. Feel Films
    Feel Films is a British film and television production company known for producing high-quality literary and genre adaptations.
  • C. Beyond Films
    Beyond Films is an Australian film distribution and production company known for handling a range of independent and international titles.
  • D. 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.
  • E. 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.
  • 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_69d8838a41f08190b0c3f79c47df5078 completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e378e999d48190bff680040dbc883d completed April 18, 2026, 12:28 p.m.
NED1 Entity disambiguation (via context triple) batch_6a007dc05bd881909c6b2e0d95622aa1 completed May 10, 2026, 12:44 p.m.
Created at: April 10, 2026, 5:17 a.m.