Triple

T6519665

Position	Surface form	Disambiguated ID	Type / Status
Subject	Library of Congress Network Development and MARC Standards Office	`E148348`	entity
Predicate	maintainsStandard	`P1371`	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.	`E606690`	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, maintainsStandard, 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, maintainsStandard, MADS (Metadata Authority Description Schema)]

A. MODS (Metadata Object Description Schema)
MODS (Metadata Object Description Schema) is an XML-based bibliographic description standard designed to provide a flexible, user-friendly alternative to MARC for describing and sharing library and cultural heritage resources.
B. 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.
C. 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.
D. MARC
MARC is a commuter rail service in Maryland that connects Washington, D.C. with Baltimore and other regional destinations.
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. 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, maintainsStandard, 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. MODS (Metadata Object Description Schema)
MODS (Metadata Object Description Schema) is an XML-based bibliographic description standard designed to provide a flexible, user-friendly alternative to MARC for describing and sharing library and cultural heritage resources.
B. 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.
C. 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.
D. MARC
MARC is a commuter rail service in Maryland that connects Washington, D.C. with Baltimore and other regional destinations.
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. chosen

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_69c6e41434108190b6c329544764dd2c`	completed	March 27, 2026, 8:09 p.m.
NEDg	Description generation	`batch_69c6e57d71ec8190b79615f11eadec26`	completed	March 27, 2026, 8:15 p.m.
NED2	Entity disambiguation (via description)	`batch_69c6e614f04c8190b25b553553895799`	completed	March 27, 2026, 8:18 p.m.

Created at: March 27, 2026, 1:45 p.m.