Triple

T18874311
Position Surface form Disambiguated ID Type / Status
Subject UN Regulation No. 51 E461644 entity
Predicate alsoKnownAs P39 FINISHED
Object R51
R51 is a United Nations vehicle regulation that sets international standards for measuring and limiting the exterior noise emissions of motor vehicles.
 E1347582 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: R51 | Statement: [UN Regulation No. 51, alsoKnownAs, R51]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: R51
Context triple: [UN Regulation No. 51, alsoKnownAs, R51]
  • A. R55
    R55 is a regional road in South Africa that runs through Gauteng, connecting areas such as Midrand with surrounding suburbs and major routes.
  • B. R5
    R5 is the U.S. Forest Service’s Pacific Southwest Region, which oversees national forests primarily in California and parts of neighboring areas.
  • C. R5
    R5 is the common shorthand name for the Renault 5, a popular compact hatchback car produced by the French manufacturer Renault.
  • D. R5
    R5 is a government office building in Oslo that forms part of Norway’s central Regjeringskvartalet complex.
  • E. R5
    R5 was a former designation for a commuter rail line in the SEPTA Regional Rail system serving the Paoli/Thorndale corridor in the Philadelphia area.
  • 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: R51
Triple: [UN Regulation No. 51, alsoKnownAs, R51]
Generated description
R51 is a United Nations vehicle regulation that sets international standards for measuring and limiting the exterior noise emissions of motor vehicles.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: R51
Target entity description: R51 is a United Nations vehicle regulation that sets international standards for measuring and limiting the exterior noise emissions of motor vehicles.
  • A. R55
    R55 is a regional road in South Africa that runs through Gauteng, connecting areas such as Midrand with surrounding suburbs and major routes.
  • B. R5
    R5 is the U.S. Forest Service’s Pacific Southwest Region, which oversees national forests primarily in California and parts of neighboring areas.
  • C. R5
    R5 is the common shorthand name for the Renault 5, a popular compact hatchback car produced by the French manufacturer Renault.
  • D. R5
    R5 is a government office building in Oslo that forms part of Norway’s central Regjeringskvartalet complex.
  • E. R5
    R5 was a former designation for a commuter rail line in the SEPTA Regional Rail system serving the Paoli/Thorndale corridor in the Philadelphia area.
  • 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_69d8dcfc3430819095ee6fc0eb4c06a5 completed April 10, 2026, 11:20 a.m.
NER Named-entity recognition batch_69e5c3cd49748190948d535918aec3de completed April 20, 2026, 6:12 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0575bfc9988190bc72525ab30cf498 completed May 14, 2026, 7:12 a.m.
NEDg Description generation batch_6a057803e99481909c6ed82014a169d0 completed May 14, 2026, 7:21 a.m.
NED2 Entity disambiguation (via description) batch_6a05785d1e08819097299cf6d9e90035 completed May 14, 2026, 7:23 a.m.
Created at: April 10, 2026, 11:57 a.m.