Triple

T6519672
Position Surface form Disambiguated ID Type / Status
Subject Library of Congress Network Development and MARC Standards Office E148348 entity
Predicate hasAbbreviation P43 FINISHED
Object NDMSO
NDMSO is the Library of Congress office responsible for developing and maintaining MARC standards and related networked library metadata frameworks.
 E605021 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: NDMSO | Statement: [Library of Congress Network Development and MARC Standards Office, hasAbbreviation, NDMSO]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: NDMSO
Context triple: [Library of Congress Network Development and MARC Standards Office, hasAbbreviation, NDMSO]
  • A. NDMC
    NDMC is the civic administrative body responsible for municipal services and infrastructure in New Delhi’s central and VIP areas.
  • B. NMS
    NMS is the commonly used abbreviation for NOVA Medical School, a medical faculty of NOVA University Lisbon in Portugal.
  • C. MSO
    MSO is the National Rail station code for Moston railway station in Greater Manchester, England.
  • D. DMS
    DMS is the acronym for the Florida Department of Management Services, the state agency responsible for overseeing business, workforce, and support services for Florida’s government.
  • E. NSM
    NSM was the stock ticker symbol for National Semiconductor, a former American semiconductor manufacturer known for its analog and mixed-signal integrated circuits.
  • 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: NDMSO
Triple: [Library of Congress Network Development and MARC Standards Office, hasAbbreviation, NDMSO]
Generated description
NDMSO is the Library of Congress office responsible for developing and maintaining MARC standards and related networked library metadata frameworks.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: NDMSO
Target entity description: NDMSO is the Library of Congress office responsible for developing and maintaining MARC standards and related networked library metadata frameworks.
  • A. NDMC
    NDMC is the civic administrative body responsible for municipal services and infrastructure in New Delhi’s central and VIP areas.
  • B. NMS
    NMS is the commonly used abbreviation for NOVA Medical School, a medical faculty of NOVA University Lisbon in Portugal.
  • C. MSO
    MSO is the National Rail station code for Moston railway station in Greater Manchester, England.
  • D. DMS
    DMS is the acronym for the Florida Department of Management Services, the state agency responsible for overseeing business, workforce, and support services for Florida’s government.
  • E. NSM
    NSM was the stock ticker symbol for National Semiconductor, a former American semiconductor manufacturer known for its analog and mixed-signal integrated circuits.
  • 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_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.