Triple

T11466378
Position Surface form Disambiguated ID Type / Status
Subject Regal Unlimited E271790 entity
Predicate competitor P1375 FINISHED
Object Cinemark Movie Club E55861 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: Cinemark Movie Club | Statement: [Regal Unlimited, competitor, Cinemark Movie Club]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cinemark Movie Club
Context triple: [Regal Unlimited, competitor, Cinemark Movie Club]
  • A. Cinemark Theatres chosen
    Cinemark Theatres is a major American movie theater chain operating multiplex cinemas across the United States and in several Latin American countries.
  • B. Regal Cinemas
    Regal Cinemas is a major American movie theater chain known for operating multiplex cinemas across the United States.
  • C. Marcus Theatres
    Marcus Theatres is a major American movie theater chain known for operating multiplex cinemas across the Midwest and other regions of the United States.
  • D. 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.
  • E. Cinepolis Luxury Cinemas
    Cinepolis Luxury Cinemas is a premium movie theater chain offering upscale amenities such as luxury seating, enhanced food and beverage service, and a high-end cinematic experience.
  • 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_69d6aae0c8d881908a5a360c0be3242e completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d822f5eb988190b309b8e309f6d1a5 completed April 9, 2026, 10:06 p.m.
NED1 Entity disambiguation (via context triple) batch_69e5e9429a308190810b485708d28617 completed April 20, 2026, 8:52 a.m.
Created at: April 8, 2026, 9:35 p.m.