Triple

T214309
Position Surface form Disambiguated ID Type / Status
Subject MARC standards E4784 entity
Predicate hasComponent P35 FINISHED
Object MARC 21 Bibliographic E4784 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: MARC 21 Bibliographic | Statement: [MARC standards, hasComponent, MARC 21 Bibliographic]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: MARC 21 Bibliographic
Context triple: [MARC standards, hasComponent, MARC 21 Bibliographic]
  • A. MARC
    MARC is a commuter rail service in Maryland that connects Washington, D.C. with Baltimore and other regional destinations.
  • B. MARC standards chosen
    MARC standards are a set of bibliographic data formats used worldwide to structure and exchange library catalog information in a consistent, machine-readable way.
  • C. BIBFRAME
    BIBFRAME (Bibliographic Framework) is a linked data model and standard developed by the Library of Congress to replace MARC for describing and sharing bibliographic information on the web.
  • D. Library of Congress Subject Headings
    Library of Congress Subject Headings is a comprehensive controlled vocabulary used by libraries worldwide to provide standardized subject access to cataloged materials.
  • E. Library of Congress Classification
    Library of Congress Classification is a comprehensive alphanumeric library classification system used primarily by academic and research libraries to organize and arrange their collections by subject.
  • 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_69a2575cb1dc8190a01ad332426dc339 completed Feb. 28, 2026, 2:47 a.m.
NER Named-entity recognition batch_69a25c32ae208190a03d504ef43ea659 completed Feb. 28, 2026, 3:08 a.m.
NED1 Entity disambiguation (via context triple) batch_69a35878158c81908fba5b3cb4bfd054 completed Feb. 28, 2026, 9:04 p.m.
Created at: Feb. 28, 2026, 2:52 a.m.