Triple

T14173226
Position Surface form Disambiguated ID Type / Status
Subject Howard Berger E351262 entity
Predicate employer P7 FINISHED
Object KNB EFX Group E389495 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: KNB EFX Group | Statement: [Howard Berger, employer, KNB EFX Group]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: KNB EFX Group
Context triple: [Howard Berger, employer, KNB EFX Group]
  • A. KNB EFX Group chosen
    KNB EFX Group is a renowned special makeup and visual effects studio known for its work on numerous high-profile horror and genre films.
  • B. Sky Studios
    Sky Studios is the original programming and production arm of European broadcaster Sky, known for creating high-profile television series and films across drama, comedy, and other genres.
  • C. Kaleidoscope Entertainment
    Kaleidoscope Entertainment is an Indian film production company known for backing notable Hindi cinema projects, including historical and socially themed films.
  • D. Digital Effects Inc.
    Digital Effects Inc. was a pioneering computer graphics and visual effects studio known for its groundbreaking work on the 1982 science-fiction film "Tron."
  • E. Xeitgeist Entertainment Group
    Xeitgeist Entertainment Group is a film production company known for backing the 2018 biographical thriller "Hotel Mumbai" and other internationally focused, socially conscious projects.
  • 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_69d8278834a08190b0f1784e58d7b99c completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de61b5dcbc8190b0cfcce5e6c6d582 completed April 14, 2026, 3:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd280656a881909c565b99e85ae9bd completed May 8, 2026, 12:02 a.m.
Created at: April 10, 2026, 1:01 a.m.