Triple

T820191
Position Surface form Disambiguated ID Type / Status
Subject Tysons Corner Center E17734 entity
Predicate hasAnchorTenant P11754 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: [Tysons Corner Center, hasAnchorTenant, AMC Theatres]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: AMC Theatres
Context triple: [Tysons Corner Center, hasAnchorTenant, 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. Regal Cinemas
    Regal Cinemas is a major American movie theater chain known for operating multiplex cinemas across 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. Cineworld Group
    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.
  • 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_69a4937bcaac8190a322524ac6f45a5a completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a4ab6698d881908d8c5d91259f97ec completed March 1, 2026, 9:11 p.m.
NED1 Entity disambiguation (via context triple) batch_69a76d8f639081909690d1ef4c98680e completed March 3, 2026, 11:23 p.m.
Created at: March 1, 2026, 7:38 p.m.