Triple

T11226278
Position Surface form Disambiguated ID Type / Status
Subject Rav-Chen E265702 entity
Predicate partOf P40 FINISHED
Object Cineworld Group cinema brands 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 cinema brands | Statement: [Rav-Chen, partOf, Cineworld Group cinema brands]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cineworld Group cinema brands
Context triple: [Rav-Chen, partOf, Cineworld Group cinema brands]
  • 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. Cineworld cinema
    Cineworld cinema is a major UK multiplex cinema chain offering mainstream film screenings and entertainment facilities.
  • C. Cinemark Theatres
    Cinemark Theatres is a major American movie theater chain operating multiplex cinemas across the United States and in several Latin American countries.
  • 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. United Cinemas
    United Cinemas is a Japanese movie theater chain operating multiplex cinemas in various locations, including major shopping and entertainment complexes.
  • 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_69d6aac656d48190b275efaa7d6074ee completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7e8ff7b40819089c835be710bc575 completed April 9, 2026, 5:59 p.m.
NED1 Entity disambiguation (via context triple) batch_69e58af8bc988190805168188ed0a6aa completed April 20, 2026, 2:10 a.m.
Created at: April 8, 2026, 9:30 p.m.