Triple

T6709087
Position Surface form Disambiguated ID Type / Status
Subject Regal Entertainment Group E153083 entity
Predicate parentOrganization P254 FINISHED
Object Cineworld Group E53486 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: Cineworld Group | Statement: [Regal Entertainment Group, parentOrganization, Cineworld Group]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cineworld Group
Context triple: [Regal Entertainment Group, parentOrganization, Cineworld Group]
  • A. Cineworld Group chosen
    Cineworld Group is a British-based multinational cinema chain operator that became one of the world’s largest theater companies following its acquisition of Regal Entertainment Group.
  • B. Cinemark Theatres
    Cinemark Theatres is a major American movie theater chain operating multiplex cinemas across the United States and in several Latin American countries.
  • C. Wanda Cinemas
    Wanda Cinemas is a major Chinese cinema chain known for operating a large network of modern movie theaters across China.
  • D. Odeon Cinemas
    Odeon Cinemas is a major British and European cinema chain known for operating numerous multiplex movie theaters across the UK and beyond.
  • E. AMC Theatres
    AMC Theatres is one of the largest movie theater chains in the world, operating multiplex cinemas across the United States and internationally.
  • 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_69c68808d8d8819087369015270788fe completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6d105b49c8190932246a727e2c513 completed March 27, 2026, 6:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7008e6b308190a3d5db2bf4a469c4 completed March 27, 2026, 10:11 p.m.
Created at: March 27, 2026, 2:06 p.m.