Triple

T1111238
Position Surface form Disambiguated ID Type / Status
Subject Buckinghamshire E10606 entity
Predicate vehicleRegistrationPrefixHistoric P7142 FINISHED
Object BU
BU is a historic vehicle registration prefix that was once used to identify motor vehicles registered in Buckinghamshire, England.
E128007 NE FINISHED

How this triple was built (5 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: BU | Statement: [Buckinghamshire, vehicleRegistrationPrefixHistoric, BU]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: BU
Context triple: [Buckinghamshire, vehicleRegistrationPrefixHistoric, BU]
  • A. BU
    BU is a major private research university in Boston, Massachusetts, known for its diverse academic programs and global student body.
  • B. BAL
    BAL is the Amtrak station code for Pennsylvania Station in Baltimore, Maryland, a major rail hub in the city’s transportation network.
  • C. BO
    BO is the two-letter ISO 3166-1 alpha-2 country code that uniquely identifies Bolivia in international standards and 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: BU
Triple: [Buckinghamshire, vehicleRegistrationPrefixHistoric, BU]
Generated description
BU is a historic vehicle registration prefix that was once used to identify motor vehicles registered in Buckinghamshire, England.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: BU
Target entity description: BU is a historic vehicle registration prefix that was once used to identify motor vehicles registered in Buckinghamshire, England.
  • A. BU
    BU is a major private research university in Boston, Massachusetts, known for its diverse academic programs and global student body.
  • B. BAL
    BAL is the Amtrak station code for Pennsylvania Station in Baltimore, Maryland, a major rail hub in the city’s transportation network.
  • C. BO
    BO is the two-letter ISO 3166-1 alpha-2 country code that uniquely identifies Bolivia in international standards and 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
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: vehicleRegistrationPrefixHistoric
Context triple: [Buckinghamshire, vehicleRegistrationPrefixHistoric, BU]
  • A. vehicleRegistrationCode
    Indicates the official registration identifier assigned to a vehicle, typically used for legal identification and record-keeping.
  • B. aircraftDesignationPrefix
    Indicates the standardized prefix used in an aircraft’s designation that conveys its type, role, or function.
  • C. registrationPrefix chosen
    Indicates that an entity has a specific registration prefix code assigned to it as part of its official registration or identification.
  • D. historicallyRecognizedAs
    Indicates that an entity has been acknowledged or designated under a particular name, status, or role during a past historical period.
  • E. historicallyBorneBy
    Indicates that an entity has carried, possessed, or used another entity (such as a name, title, or symbol) at some point in the past.
  • F. None of above.

Provenance (6 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_69a493252a648190ac48f8742474a5e8 completed March 1, 2026, 7:27 p.m.
NER Named-entity recognition batch_69a4bbd92a8c8190a16e55f3f739010f completed March 1, 2026, 10:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac53935d108190955343cd1d3716b0 completed March 7, 2026, 4:34 p.m.
NEDg Description generation batch_69ac5436b8688190b9d13a6920a218f6 completed March 7, 2026, 4:37 p.m.
NED2 Entity disambiguation (via description) batch_69ac548b363881908de3588d34c4960c completed March 7, 2026, 4:38 p.m.
PD Predicate disambiguation batch_69a4bb42990c819080db96478fd4977e completed March 1, 2026, 10:18 p.m.
Created at: March 1, 2026, 7:43 p.m.