Triple

T6519664
Position Surface form Disambiguated ID Type / Status
Subject Library of Congress Network Development and MARC Standards Office E148348 entity
Predicate developsStandard P73 FINISHED
Object MADS (Metadata Authority Description Schema)
MADS (Metadata Authority Description Schema) is an XML-based schema used primarily by libraries and related institutions to structure and manage authority data for names, subjects, and other controlled vocabularies.
 E27068 NE FINISHED

How this triple was built (4 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: MADS (Metadata Authority Description Schema) | Statement: [Library of Congress Network Development and MARC Standards Office, developsStandard, MADS (Metadata Authority Description Schema)]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: MADS (Metadata Authority Description Schema)
Context triple: [Library of Congress Network Development and MARC Standards Office, developsStandard, MADS (Metadata Authority Description Schema)]
  • A. S-100 metadata framework
    The S-100 metadata framework is an IHO-developed standard that defines a flexible, interoperable structure for describing and managing geospatial and hydrographic data within the broader S-100 universal hydrographic data model.
  • B. 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.
  • C. MARC
    MARC is a commuter rail service in Maryland that connects Washington, D.C. with Baltimore and other regional destinations.
  • D. METS
    METS (Metadata Encoding and Transmission Standard) is an XML-based standard for encoding descriptive, administrative, and structural metadata for complex digital library objects.
  • E. 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.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: MADS (Metadata Authority Description Schema)
Triple: [Library of Congress Network Development and MARC Standards Office, developsStandard, MADS (Metadata Authority Description Schema)]
Generated description
MADS (Metadata Authority Description Schema) is an XML-based schema used primarily by libraries and related institutions to structure and manage authority data for names, subjects, and other controlled vocabularies.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: MADS (Metadata Authority Description Schema)
Target entity description: MADS (Metadata Authority Description Schema) is an XML-based schema used primarily by libraries and related institutions to structure and manage authority data for names, subjects, and other controlled vocabularies.
  • A. S-100 metadata framework
    The S-100 metadata framework is an IHO-developed standard that defines a flexible, interoperable structure for describing and managing geospatial and hydrographic data within the broader S-100 universal hydrographic data model.
  • B. 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.
  • C. MARC
    MARC is a commuter rail service in Maryland that connects Washington, D.C. with Baltimore and other regional destinations.
  • D. METS chosen
    METS (Metadata Encoding and Transmission Standard) is an XML-based standard for encoding descriptive, administrative, and structural metadata for complex digital library objects.
  • E. 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.
  • F. None of above.

Provenance (5 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_69c687e68e748190baceb9298f32d3ed completed March 27, 2026, 1:36 p.m.
NER Named-entity recognition batch_69c6ac11d0e481908103c4b51de9521e completed March 27, 2026, 4:10 p.m.
NED1 Entity disambiguation (via context triple) batch_69c6d51af5308190928c97ceb5d5fa2d completed March 27, 2026, 7:06 p.m.
NEDg Description generation batch_69c6d6d9af148190ad9cd2cc31a70bb7 completed March 27, 2026, 7:13 p.m.
NED2 Entity disambiguation (via description) batch_69c6d98506b88190aae3b4d887744648 completed March 27, 2026, 7:24 p.m.
Created at: March 27, 2026, 1:45 p.m.