Triple

T2598509
Position Surface form Disambiguated ID Type / Status
Subject Louis B. Mayer E58288 entity
Predicate workLocation P7 FINISHED
Object Culver City E238374 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: Culver City | Statement: [Louis B. Mayer, workLocation, Culver City]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Culver City
Context triple: [Louis B. Mayer, workLocation, Culver City]
  • A. Culver City chosen
    Culver City is an independent city in western Los Angeles County, California, known for its historic film and television studios and vibrant arts and dining scene.
  • B. West Hollywood
    West Hollywood is an independent city in Los Angeles County known for its vibrant nightlife, LGBTQ+ community, and iconic Sunset Strip.
  • C. Los Feliz
    Los Feliz is a historic and trendy neighborhood in central Los Angeles known for its hillside homes, proximity to Griffith Park, and vibrant dining and nightlife scene.
  • D. Encino
    Encino is a residential neighborhood in the San Fernando Valley region of Los Angeles known for its suburban character, affluent homes, and proximity to major city amenities.
  • E. Santa Monica
    Santa Monica is a coastal city in western Los Angeles County, California, known for its iconic pier, beaches, and vibrant tourism and entertainment scene.
  • 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_69ab4ac14040819098b13f4a27d5c8ff completed March 6, 2026, 9:44 p.m.
NER Named-entity recognition batch_69abd4563b8c8190934616651e93654c completed March 7, 2026, 7:31 a.m.
NED1 Entity disambiguation (via context triple) batch_69b31a46eea081909e1faf639f7789ff completed March 12, 2026, 7:55 p.m.
Created at: March 6, 2026, 9:49 p.m.