Triple

T1932682
Position Surface form Disambiguated ID Type / Status
Subject Legacy Recordings E40979 entity
Predicate hasPrimaryBusinessModel P16009 FINISHED
Object exploitation of existing recordings LITERAL 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: exploitation of existing recordings | Statement: [Legacy Recordings, hasPrimaryBusinessModel, exploitation of existing recordings]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasPrimaryBusinessModel
Context triple: [Legacy Recordings, hasPrimaryBusinessModel, exploitation of existing recordings]
  • A. hasUnderlyingCompanyBusinessModel
    Indicates that one entity possesses or is based on a specific company business model that underlies its structure, operations, or value creation.
  • B. usesBusinessModel
    Indicates that one entity operates according to, or applies in practice, the business model defined or provided by another entity.
  • C. hasBusiness
    Indicates that one entity owns, operates, or is formally associated with a business entity.
  • D. hasMajorBusinessLine chosen
    Indicates that an entity conducts a primary or significant line of business in a specified area, sector, or activity.
  • E. businessModelFocus
    Indicates that one entity’s business model is centered on, tailored to, or primarily oriented around another entity or specific focus area.
  • F. None of above.

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_69a8864711648190b07bed24ed76258e completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69abb299f3c48190a5021d320ded4405 completed March 7, 2026, 5:07 a.m.
PD Predicate disambiguation batch_69abafeec6f881909d47acb966683279 completed March 7, 2026, 4:56 a.m.
Created at: March 4, 2026, 7:35 p.m.