Triple

T1275086
Position Surface form Disambiguated ID Type / Status
Subject Basel-Landschaft E15795 entity
Predicate vehicleRegistrationCode P1173 FINISHED
Object BL
BL is the vehicle registration code used on license plates for the Swiss canton of Basel-Landschaft.
 E145802 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: BL | Statement: [Basel-Landschaft, vehicleRegistrationCode, BL]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: BL
Context triple: [Basel-Landschaft, vehicleRegistrationCode, BL]
  • A. BAL
    BAL is the Amtrak station code for Pennsylvania Station in Baltimore, Maryland, a major rail hub in the city’s transportation network.
  • B. Bal
    Bal is the given name of Bal Gangadhar Tilak, a prominent Indian nationalist leader and social reformer of the late 19th and early 20th centuries.
  • C. BEL
    BEL is the three-letter ISO 3166-1 alpha-3 country code that uniquely identifies Belgium in international standards and data systems.
  • D. BR
    BR is the upper house of Austria’s parliament, representing the federal states in the legislative process.
  • E. BR
    BR is the two-letter ISO 3166-1 alpha-2 country code that uniquely identifies Brazil in international standards and systems.
  • 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: BL
Triple: [Basel-Landschaft, vehicleRegistrationCode, BL]
Generated description
BL is the vehicle registration code used on license plates for the Swiss canton of Basel-Landschaft.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: BL
Target entity description: BL is the vehicle registration code used on license plates for the Swiss canton of Basel-Landschaft.
  • A. BAL
    BAL is the Amtrak station code for Pennsylvania Station in Baltimore, Maryland, a major rail hub in the city’s transportation network.
  • B. Bal
    Bal is the given name of Bal Gangadhar Tilak, a prominent Indian nationalist leader and social reformer of the late 19th and early 20th centuries.
  • C. BEL
    BEL is the three-letter ISO 3166-1 alpha-3 country code that uniquely identifies Belgium in international standards and data systems.
  • D. BR
    BR is the upper house of Austria’s parliament, representing the federal states in the legislative process.
  • E. BR
    BR is the two-letter ISO 3166-1 alpha-2 country code that uniquely identifies Brazil in international standards and systems.
  • 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_69a4935a94308190bb92555b79032824 completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a4c06ee22081908141868b57596e35 completed March 1, 2026, 10:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69aca2f6c8a08190ac6b1f477388adbb completed March 7, 2026, 10:13 p.m.
NEDg Description generation batch_69aca38229108190b8cc2e0ef5bc8667 completed March 7, 2026, 10:15 p.m.
NED2 Entity disambiguation (via description) batch_69aca40068f08190a49f9cbb5c78b471 completed March 7, 2026, 10:17 p.m.
Created at: March 1, 2026, 7:50 p.m.