Triple

T5815449
Position Surface form Disambiguated ID Type / Status
Subject BMG Korea E128973 entity
Predicate affiliation P10 FINISHED
Object BMG E128973 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: BMG | Statement: [BMG Korea, affiliation, BMG]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: BMG
Context triple: [BMG Korea, affiliation, BMG]
  • A. BMG
    BMG is the commonly used abbreviation for Germany’s Federal Ministry of Health.
  • B. BMG
    BMG is a major global music company known for its music publishing and recorded music services, representing a wide range of international artists and catalogs.
  • C. BMG Classics
    BMG Classics was the classical music division and record label of Bertelsmann Music Group, known for releasing and distributing classical recordings by major orchestras, conductors, and soloists.
  • D. BMG India
    BMG India was the Indian division of the global music company Bertelsmann Music Group, responsible for producing and distributing music in the Indian market.
  • E. BMG Korea chosen
    BMG Korea was the South Korean branch of the global music company Bertelsmann Music Group, responsible for producing and distributing music in the Korean market.
  • 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_69c0084788848190bcf71f6bc5d71597 completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c0336344148190bcf417c0b9617cb9 completed March 22, 2026, 6:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69c0984c5f14819096dfabce4a83e332 completed March 23, 2026, 1:33 a.m.
Created at: March 22, 2026, 3:53 p.m.