Triple

T1034249
Position Surface form Disambiguated ID Type / Status
Subject Basel-Stadt E22322 entity
Predicate vehicleRegistrationCode P1173 FINISHED
Object BS
BS is the vehicle registration code used on license plates for the Swiss canton of Basel-Stadt.
 E120072 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: BS | Statement: [Basel-Stadt, vehicleRegistrationCode, BS]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: BS
Context triple: [Basel-Stadt, vehicleRegistrationCode, BS]
  • 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 New York Stock Exchange ticker symbol for The Boeing Company, a major American aerospace and defense manufacturer.
  • C. BSC
    BSC is an acronym commonly referring to British Security Coordination, a covert World War II intelligence organization established by the United Kingdom in North America.
  • D. B
    B is the designation of one of the main lines of the Paris RER commuter rail network, serving a major north–south axis through the Île-de-France region.
  • E. B
    B is the vehicle registration code used on license plates for Berlin, Germany.
  • 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: BS
Triple: [Basel-Stadt, vehicleRegistrationCode, BS]
Generated description
BS is the vehicle registration code used on license plates for the Swiss canton of Basel-Stadt.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: BS
Target entity description: BS is the vehicle registration code used on license plates for the Swiss canton of Basel-Stadt.
  • 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 New York Stock Exchange ticker symbol for The Boeing Company, a major American aerospace and defense manufacturer.
  • C. BSC
    BSC is an acronym commonly referring to British Security Coordination, a covert World War II intelligence organization established by the United Kingdom in North America.
  • D. B
    B is the designation of one of the main lines of the Paris RER commuter rail network, serving a major north–south axis through the Île-de-France region.
  • E. B
    B is the vehicle registration code used on license plates for Berlin, Germany.
  • 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_69a493d848848190aed4011b34b2e8d3 completed March 1, 2026, 7:30 p.m.
NER Named-entity recognition batch_69a4b814c16c8190ac4d20feecdadbae completed March 1, 2026, 10:05 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac3bc15a6c81909a71bf17b5cd4019 completed March 7, 2026, 2:52 p.m.
NEDg Description generation batch_69ac3c7d16748190a95aaffd04a867b3 completed March 7, 2026, 2:55 p.m.
NED2 Entity disambiguation (via description) batch_69ac3ce827b88190a5de06c695ad4ecb completed March 7, 2026, 2:57 p.m.
Created at: March 1, 2026, 7:41 p.m.