Triple

T15463592
Position Surface form Disambiguated ID Type / Status
Subject Metreon E371967 entity
Predicate hasTenant P3277 FINISHED
Object AMC Theatres E55106 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: AMC Theatres | Statement: [Metreon, hasTenant, AMC Theatres]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: AMC Theatres
Context triple: [Metreon, hasTenant, AMC Theatres]
  • A. AMC Theatres chosen
    AMC Theatres is one of the largest movie theater chains in the world, operating multiplex cinemas across the United States and internationally.
  • 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. United Cinemas
    United Cinemas is a Japanese movie theater chain operating multiplex cinemas in various locations, including major shopping and entertainment complexes.
  • D. 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.
  • E. Nimax Theatres
    Nimax Theatres is a London-based theatre operating company that owns and manages several prominent West End venues.
  • 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_69d85cc8bd308190886949510b42e764 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e03f1927708190a0d2b63e75469a0e completed April 16, 2026, 1:44 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff2cff942081908a2f5351079666a3 completed May 9, 2026, 12:47 p.m.
Created at: April 10, 2026, 3:33 a.m.