Triple

T2123847
Position Surface form Disambiguated ID Type / Status
Subject Duisburg E43985 entity
Predicate vehicleRegistrationCode P1173 FINISHED
Object DU
DU is the vehicle registration code used on license plates for the German city of Duisburg.
 E236405 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: DU | Statement: [Duisburg, vehicleRegistrationCode, DU]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: DU
Context triple: [Duisburg, vehicleRegistrationCode, DU]
  • A. DU
    DU is a premier public central university in India, renowned for its diverse academic programs and large collegiate system based in New Delhi.
  • B. CU
    CU is the two-letter ISO 3166-1 alpha-2 country code assigned to Cuba.
  • C. DUS
    DUS is the three-letter IATA code for Düsseldorf Airport, a major international airport in western Germany.
  • D. BU
    BU is a major private research university in Boston, Massachusetts, known for its diverse academic programs and global student body.
  • E. BU
    BU is a historic vehicle registration prefix that was once used to identify motor vehicles registered in Buckinghamshire, England.
  • 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: DU
Triple: [Duisburg, vehicleRegistrationCode, DU]
Generated description
DU is the vehicle registration code used on license plates for the German city of Duisburg.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: DU
Target entity description: DU is the vehicle registration code used on license plates for the German city of Duisburg.
  • A. DU
    DU is a premier public central university in India, renowned for its diverse academic programs and large collegiate system based in New Delhi.
  • B. CU
    CU is the two-letter ISO 3166-1 alpha-2 country code assigned to Cuba.
  • C. DUS
    DUS is the three-letter IATA code for Düsseldorf Airport, a major international airport in western Germany.
  • D. BU
    BU is a major private research university in Boston, Massachusetts, known for its diverse academic programs and global student body.
  • E. BU
    BU is a historic vehicle registration prefix that was once used to identify motor vehicles registered in Buckinghamshire, England.
  • 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_69a88717cfe48190b7ecdd68c824848a completed March 4, 2026, 7:25 p.m.
NER Named-entity recognition batch_69abbb55cb2c8190aab8199da3335032 completed March 7, 2026, 5:44 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae519bfdb08190a7b715fbc5fd3f41 completed March 9, 2026, 4:50 a.m.
NEDg Description generation batch_69ae521c7810819086b88bb5f062597e completed March 9, 2026, 4:52 a.m.
NED2 Entity disambiguation (via description) batch_69ae52e79c788190bbe6eb5baba08a71 completed March 9, 2026, 4:56 a.m.
Created at: March 4, 2026, 7:44 p.m.