Triple

T2664150
Position Surface form Disambiguated ID Type / Status
Subject Mark Burg E55591 entity
Predicate workLocation P7 FINISHED
Object Hollywood E247 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: Hollywood | Statement: [Mark Burg, workLocation, Hollywood]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hollywood
Context triple: [Mark Burg, workLocation, Hollywood]
  • A. Hollywood
    Hollywood is a residential neighborhood in the city of College Park, Maryland, known for its suburban character and proximity to the University of Maryland.
  • B. Hollywood
    Hollywood is a residential neighborhood in Homewood, Alabama, known for its historic homes and suburban character just outside Birmingham.
  • C. Hollywood
    Hollywood is a coastal city in southeastern Florida known for its beaches, boardwalk, and proximity to Miami.
  • D. Hollywood chosen
    Hollywood is a famous Los Angeles neighborhood internationally recognized as the historic center of the American film and entertainment industry.
  • E. Universal City, California
    Universal City, California is an unincorporated community in Los Angeles County best known as the home of the Universal Studios film studio and theme park complex.
  • 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_69ab49e54de48190be708cd1cf8be073 completed March 6, 2026, 9:40 p.m.
NER Named-entity recognition batch_69abd96dba44819085c3e651afba7806 completed March 7, 2026, 7:53 a.m.
NED1 Entity disambiguation (via context triple) batch_69af98c2bde8819085fbe1e5221be88d completed March 10, 2026, 4:06 a.m.
Created at: March 6, 2026, 9:54 p.m.