Triple

T21909076
Position Surface form Disambiguated ID Type / Status
Subject Kathmandu District E541014 entity
Predicate hasVehicleRegistrationCode P1173 FINISHED
Object BA
BA is the vehicle registration code assigned to motor vehicles registered in Kathmandu District, Nepal.
E1508232 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: BA | Statement: [Kathmandu District, hasVehicleRegistrationCode, BA]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: BA
Context triple: [Kathmandu District, hasVehicleRegistrationCode, BA]
  • A. BA
    BA is the New York Stock Exchange ticker symbol for The Boeing Company, a major American aerospace and defense manufacturer.
  • B. BA
    BA is a common abbreviation for Broken Arrow, a suburban city in northeastern Oklahoma.
  • C. BA
    BA is the station code for Bathurst station on the Toronto Transit Commission subway system.
  • D. BA
    BA is the former stock ticker symbol for Bell Aliant, a Canadian telecommunications company that provided internet, phone, and TV services primarily in Atlantic Canada before being acquired by Bell Canada.
  • E. BA
    BA is the station code for Balderas, a metro station in Mexico City’s rapid transit system.
  • 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: BA
Triple: [Kathmandu District, hasVehicleRegistrationCode, BA]
Generated description
BA is the vehicle registration code assigned to motor vehicles registered in Kathmandu District, Nepal.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: BA
Target entity description: BA is the vehicle registration code assigned to motor vehicles registered in Kathmandu District, Nepal.
  • A. BA
    BA is the vehicle registration code used on license plates for cars registered in Bratislava, the capital city of Slovakia.
  • B. BA
    BA is the vehicle registration code assigned to motor vehicles registered in Pasaman Regency, Indonesia.
  • C. BA
    BA is the vehicle registration code assigned to motor vehicles registered in Agam Regency, Indonesia.
  • D. BA
    BA is the vehicle registration code used on license plates for the city and district of Bamberg in Upper Franconia, Germany.
  • E. BA
    BA is the regional vehicle registration code assigned to motor vehicles registered in Pesisir Selatan Regency, Indonesia.
  • 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_69e0c47b4e8c81908c8076eaa4c8e4f2 completed April 16, 2026, 11:14 a.m.
NER Named-entity recognition batch_69f121d8c3108190a178ec6b3857da3f completed April 28, 2026, 9:08 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0a5a0d542c8190879307fd9228d2b6 completed May 18, 2026, 12:15 a.m.
NEDg Description generation batch_6a0a5a8228a4819082857231202487e6 completed May 18, 2026, 12:17 a.m.
NED2 Entity disambiguation (via description) batch_6a0a5af2b0188190b6221d1a2f94c5af completed May 18, 2026, 12:18 a.m.
Created at: April 16, 2026, 7:39 p.m.