Triple

T6377975
Position Surface form Disambiguated ID Type / Status
Subject Netherlands Marine Corps E143511 entity
Predicate shortName P43 FINISHED
Object RNLMC
The RNLMC is the Royal Netherlands Marine Corps, an elite amphibious infantry force of the Dutch armed forces.
 E587715 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: RNLMC | Statement: [Netherlands Marine Corps, shortName, RNLMC]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: RNLMC
Context triple: [Netherlands Marine Corps, shortName, RNLMC]
  • A. RMLNLU
    RMLNLU is a premier public law university located in Lucknow, Uttar Pradesh, India, offering undergraduate and postgraduate legal education and research programs.
  • B. NNMC
    NNMC is the commonly used abbreviation for the National Naval Medical Center, the former U.S. Navy flagship hospital in Bethesda, Maryland.
  • C. LIMC
    LIMC is the ICAO airport code for Milan Malpensa Airport, a major international airport serving the Milan metropolitan area in Italy.
  • D. NMC
    NMC is the abbreviated name commonly used for the Nagpur Municipal Corporation, the civic governing body of Nagpur city in Maharashtra, India.
  • E. RMAC
    RMAC is the abbreviated name of the Royal Mint Advisory Committee, the expert body that advises on the artistic and design aspects of UK coins, medals, seals, and official decorations.
  • 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: RNLMC
Triple: [Netherlands Marine Corps, shortName, RNLMC]
Generated description
The RNLMC is the Royal Netherlands Marine Corps, an elite amphibious infantry force of the Dutch armed forces.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: RNLMC
Target entity description: The RNLMC is the Royal Netherlands Marine Corps, an elite amphibious infantry force of the Dutch armed forces.
  • A. RMLNLU
    RMLNLU is a premier public law university located in Lucknow, Uttar Pradesh, India, offering undergraduate and postgraduate legal education and research programs.
  • B. NNMC
    NNMC is the commonly used abbreviation for the National Naval Medical Center, the former U.S. Navy flagship hospital in Bethesda, Maryland.
  • C. LIMC
    LIMC is the ICAO airport code for Milan Malpensa Airport, a major international airport serving the Milan metropolitan area in Italy.
  • D. NMC
    NMC is the abbreviated name commonly used for the Nagpur Municipal Corporation, the civic governing body of Nagpur city in Maharashtra, India.
  • E. RMAC
    RMAC is the abbreviated name of the Royal Mint Advisory Committee, the expert body that advises on the artistic and design aspects of UK coins, medals, seals, and official decorations.
  • 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_69c008d9f4348190ab598a2913259a1c completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c0683ed0788190b00f626c76a71ea2 completed March 22, 2026, 10:07 p.m.
NED1 Entity disambiguation (via context triple) batch_69c62da390c081908690ec716aed8fea completed March 27, 2026, 7:11 a.m.
NEDg Description generation batch_69c62dfff4e08190a4491fdef022acb6 completed March 27, 2026, 7:13 a.m.
NED2 Entity disambiguation (via description) batch_69c62e7c07a88190a366ff23605cb161 completed March 27, 2026, 7:15 a.m.
Created at: March 22, 2026, 4:33 p.m.