Triple

T3264694
Position Surface form Disambiguated ID Type / Status
Subject New Carrollton, Maryland E68495 entity
Predicate railOperator P522 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: [New Carrollton, Maryland, railOperator, MARC]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: MARC
Context triple: [New Carrollton, Maryland, railOperator, 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. 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.
  • D. Korean MARC
    Korean MARC is a national bibliographic metadata standard used in South Korea for cataloging library and information resources.
  • E. Library of Congress Network Development and MARC Standards Office
    The Library of Congress Network Development and MARC Standards Office is the unit of the Library of Congress responsible for developing and maintaining key bibliographic standards and networked library data models used worldwide.
  • 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_69ad8590444081909e8107a8aeef3a23 completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adafcb2da08190a7f4fefdfe6d0098 completed March 8, 2026, 5:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69b28ee82a78819082582a24bac97f44 completed March 12, 2026, 10:01 a.m.
Created at: March 8, 2026, 3:09 p.m.