Triple

T759242
Position Surface form Disambiguated ID Type / Status
Subject Maryland Area Regional Commuter E16028 entity
Predicate abbreviation P43 FINISHED
Object MARC E16027 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 | Statement: [Maryland Area Regional Commuter, abbreviation, MARC]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: MARC
Context triple: [Maryland Area Regional Commuter, abbreviation, MARC]
  • A. MARC chosen
    MARC is a commuter rail service in Maryland that connects Washington, D.C. with Baltimore and other regional destinations.
  • B. MARC standards
    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. Z39.50
    Z39.50 is a client-server protocol used primarily by libraries and information services to search and retrieve bibliographic and related data from remote databases in a standardized way.
  • E. METS
    METS (Metadata Encoding and Transmission Standard) is an XML-based standard for encoding descriptive, administrative, and structural metadata for complex digital library objects.
  • 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_69a493684ee48190bd43b7c78da4aec8 completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a4a67f9778819098d3c144dd26b976 completed March 1, 2026, 8:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69a65e44b9c88190a4481c28499860d7 completed March 3, 2026, 4:06 a.m.
Created at: March 1, 2026, 7:37 p.m.