Triple

T9068361
Position Surface form Disambiguated ID Type / Status
Subject LCGFT E217299 entity
Predicate supportsStandard P1587 FINISHED
Object MARC 21 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 | Statement: [LCGFT, supportsStandard, MARC 21]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: MARC 21
Context triple: [LCGFT, supportsStandard, MARC 21]
  • A. MARC
    MARC is a regional planning and coordination agency serving the Kansas City metropolitan area, focusing on transportation, emergency services, environmental planning, and community development.
  • B. MARC
    MARC is a commuter rail service in Maryland that connects Washington, D.C. with Baltimore and other regional destinations.
  • C. 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.
  • D. Functional Requirements for Bibliographic Records
    Functional Requirements for Bibliographic Records (FRBR) is a conceptual model developed by the International Federation of Library Associations to define user-focused tasks and relationships for bibliographic records in library catalogs.
  • E. Maschinelles Austauschformat für Bibliotheken
    Maschinelles Austauschformat für Bibliotheken (MAB) is a German machine-readable data exchange format historically used by libraries to encode and share bibliographic and authority records.
  • 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_69ca83d5a7f48190b16c1e59bd43ede0 completed March 30, 2026, 2:08 p.m.
NER Named-entity recognition batch_69cc94bf4f2881908c881e6ee7203994 completed April 1, 2026, 3:45 a.m.
NED1 Entity disambiguation (via context triple) batch_69cffddc5c288190b18c2ae1aece4ed6 completed April 3, 2026, 5:50 p.m.
Created at: March 30, 2026, 7:11 p.m.