Triple

T2482997
Position Surface form Disambiguated ID Type / Status
Subject Cinemark Theatres E55861 entity
Predicate brand P1500 FINISHED
Object Rave Cinemas
Rave Cinemas is a movie theater chain in the United States that operates multiplex cinemas for mainstream film releases.
 E284941 NE FINISHED

How this triple was built (4 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: Rave Cinemas | Statement: [Cinemark Theatres, brand, Rave Cinemas]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Rave Cinemas
Context triple: [Cinemark Theatres, brand, Rave Cinemas]
  • A. Regal Cinemas
    Regal Cinemas is a major American movie theater chain known for operating multiplex cinemas across the United States.
  • B. Arclight Cinemas
    Arclight Cinemas was a premium movie theater chain based in Los Angeles, known for its upscale amenities, reserved seating, and operation of the iconic Cinerama Dome.
  • C. Reel Cinemas
    Reel Cinemas is a popular cinema chain in Dubai known for its modern multiplex theaters and premium movie-going experiences.
  • D. Ikspiari Cinema Complex
    Ikspiari Cinema Complex is a multi-screen movie theater located within the Ikspiari shopping and entertainment district at Tokyo Disney Resort in Japan.
  • E. Cinema City
    Cinema City is a European cinema chain brand operated by Cineworld Group, known for its multiplex movie theaters across several countries.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Rave Cinemas
Triple: [Cinemark Theatres, brand, Rave Cinemas]
Generated description
Rave Cinemas is a movie theater chain in the United States that operates multiplex cinemas for mainstream film releases.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Rave Cinemas
Target entity description: Rave Cinemas is a movie theater chain in the United States that operates multiplex cinemas for mainstream film releases.
  • A. Regal Cinemas
    Regal Cinemas is a major American movie theater chain known for operating multiplex cinemas across the United States.
  • B. Arclight Cinemas
    Arclight Cinemas was a premium movie theater chain based in Los Angeles, known for its upscale amenities, reserved seating, and operation of the iconic Cinerama Dome.
  • C. Reel Cinemas
    Reel Cinemas is a popular cinema chain in Dubai known for its modern multiplex theaters and premium movie-going experiences.
  • D. Ikspiari Cinema Complex
    Ikspiari Cinema Complex is a multi-screen movie theater located within the Ikspiari shopping and entertainment district at Tokyo Disney Resort in Japan.
  • E. Cinema City
    Cinema City is a European cinema chain brand operated by Cineworld Group, known for its multiplex movie theaters across several countries.
  • F. None of above. chosen

Provenance (5 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_69ab49e670a88190b928e08302381710 completed March 6, 2026, 9:40 p.m.
NER Named-entity recognition batch_69abd163378481908b75f2f5de0e89c6 completed March 7, 2026, 7:18 a.m.
NED1 Entity disambiguation (via context triple) batch_69af98a63a44819092c017b8624e3dc8 completed March 10, 2026, 4:05 a.m.
NEDg Description generation batch_69af98f5d8f08190bdb7404e4534b11b completed March 10, 2026, 4:07 a.m.
NED2 Entity disambiguation (via description) batch_69af995414bc8190923f75ef2d0a1163 completed March 10, 2026, 4:08 a.m.
Created at: March 6, 2026, 9:45 p.m.