Triple

T14454735
Position Surface form Disambiguated ID Type / Status
Subject Things Change E358426 entity
Predicate productionCompany P490 FINISHED
Object Filmhaus E967181 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: Filmhaus | Statement: [Things Change, productionCompany, Filmhaus]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Filmhaus
Context triple: [Things Change, productionCompany, Filmhaus]
  • A. Filmhaus chosen
    Filmhaus is a film production company known for producing the psychological thriller "House of Games."
  • B. The Film House
    The Film House is a film and television production company known for developing and producing screen content such as the project "Newsfront."
  • C. Eros Cinema
    Eros Cinema is a historic Art Deco movie theater and landmark in Mumbai, India, known for its distinctive architecture and cultural significance.
  • D. Casa del Cinema
    Casa del Cinema is a cultural center in Rome dedicated to film screenings, festivals, and cinematic events, located within the Villa Borghese gardens.
  • E. Cinema de Lux
    Cinema de Lux is a premium movie theater complex known for offering an upscale cinema experience with enhanced amenities and comfort.
  • 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_69d82794dfa081909b9134ad2e32244b completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de91a8bf088190abf5fd4f646b8c62 completed April 14, 2026, 7:12 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd648f56608190b6d55c592c088575 completed May 8, 2026, 4:20 a.m.
Created at: April 10, 2026, 1:19 a.m.