Triple

T18874632
Position Surface form Disambiguated ID Type / Status
Subject Working Party on Automated/Autonomous and Connected Vehicles E461651 entity
Predicate shortName P43 FINISHED
Object GRVA
GRVA is a United Nations working party focused on regulations and standards for automated, autonomous, and connected vehicles.
 E1347594 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: GRVA | Statement: [Working Party on Automated/Autonomous and Connected Vehicles, shortName, GRVA]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: GRVA
Context triple: [Working Party on Automated/Autonomous and Connected Vehicles, shortName, GRVA]
  • A. GVRA
    GVRA is a state agency in Georgia that provides vocational rehabilitation and related services to help individuals with disabilities prepare for, obtain, and maintain employment.
  • B. GRA
    GRA is the ring-shaped orbital motorway encircling Rome, Italy, serving as a major traffic artery for the metropolitan area.
  • C. GRV
    GRV is the IATA airport code for Grozny Airport, the main air gateway serving Grozny in the Chechen Republic of Russia.
  • D. GRV
    GRV is the National Rail station code for Gravesend railway station in Kent, England.
  • E. GVAP
    GVAP is a comprehensive global framework developed to improve access to vaccines, strengthen immunization systems, and reduce vaccine-preventable diseases worldwide.
  • 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: GRVA
Triple: [Working Party on Automated/Autonomous and Connected Vehicles, shortName, GRVA]
Generated description
GRVA is a United Nations working party focused on regulations and standards for automated, autonomous, and connected vehicles.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: GRVA
Target entity description: GRVA is a United Nations working party focused on regulations and standards for automated, autonomous, and connected vehicles.
  • A. GVRA
    GVRA is a state agency in Georgia that provides vocational rehabilitation and related services to help individuals with disabilities prepare for, obtain, and maintain employment.
  • B. GRA
    GRA is the ring-shaped orbital motorway encircling Rome, Italy, serving as a major traffic artery for the metropolitan area.
  • C. GRV
    GRV is the IATA airport code for Grozny Airport, the main air gateway serving Grozny in the Chechen Republic of Russia.
  • D. GRV
    GRV is the National Rail station code for Gravesend railway station in Kent, England.
  • E. GVAP
    GVAP is a comprehensive global framework developed to improve access to vaccines, strengthen immunization systems, and reduce vaccine-preventable diseases worldwide.
  • 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.