Triple

T11651051
Position Surface form Disambiguated ID Type / Status
Subject BKS E276903 entity
Predicate industryOfUnderlyingIssuer P100187 FINISHED
Object bookselling 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: bookselling | Statement: [BKS, industryOfUnderlyingIssuer, bookselling]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: industryOfUnderlyingIssuer
Context triple: [BKS, industryOfUnderlyingIssuer, bookselling]
  • A. industryOfUnderlyingCompany
    Indicates the industry sector in which the underlying company associated with this entity operates.
  • B. underlyingAsset
    Indicates that one asset serves as the fundamental reference or basis for the value, performance, or contractual terms of another financial instrument or derivative.
  • C. underlyingConstituentsType
    Indicates the type or category of fundamental components that make up or underlie a given entity or structure.
  • D. underlyingCompanyType
    Indicates the classification or category of company that forms the basis or source for another related entity or instrument.
  • E. hasUnderlyingIssuer
    Indicates that one entity serves as the fundamental or primary issuer behind another entity, such as a financial instrument or structured product.
  • F. None of above. chosen

Provenance (4 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_69d6aafbb3c081908a9cdb4ecb8d981d completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d8a2cea9308190a13f7dd995ea07a4 completed April 10, 2026, 7:12 a.m.
PD Predicate disambiguation batch_69d85ddc780481909a3bc63832fe2bd2 completed April 10, 2026, 2:18 a.m.
PDg Predicate description generation batch_69d87f30642c8190ad94fa061cde186b completed April 10, 2026, 4:40 a.m.
Created at: April 8, 2026, 9:39 p.m.