Triple

T16210026
Position Surface form Disambiguated ID Type / Status
Subject Province of Udine E393436 entity
Predicate vehicleRegistrationCode P1173 FINISHED
Object UD
UD is the vehicle registration code used on license plates for vehicles registered in the Province of Udine in northeastern Italy.
 E1201016 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: UD | Statement: [Province of Udine, vehicleRegistrationCode, UD]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: UD
Context triple: [Province of Udine, vehicleRegistrationCode, UD]
  • A. UD
    UD is the commonly used Swedish abbreviation for the Ministry for Foreign Affairs, the government body responsible for Sweden’s foreign policy and international relations.
  • B. DU
    DU is a premier public central university in India, renowned for its diverse academic programs and large collegiate system based in New Delhi.
  • C. DU
    DU is the vehicle registration code used on license plates for the German city of Duisburg.
  • D. DU
    DU is an automated underwriting system developed by Fannie Mae that evaluates mortgage loan applications and assesses borrower credit risk.
  • E. DU
    DU is the commonly used abbreviation for the University of Denver, particularly associated with its Denver Pioneers athletic programs.
  • 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: UD
Triple: [Province of Udine, vehicleRegistrationCode, UD]
Generated description
UD is the vehicle registration code used on license plates for vehicles registered in the Province of Udine in northeastern Italy.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: UD
Target entity description: UD is the vehicle registration code used on license plates for vehicles registered in the Province of Udine in northeastern Italy.
  • A. UD
    UD is the commonly used Swedish abbreviation for the Ministry for Foreign Affairs, the government body responsible for Sweden’s foreign policy and international relations.
  • B. DU
    DU is a premier public central university in India, renowned for its diverse academic programs and large collegiate system based in New Delhi.
  • C. DU
    DU is the vehicle registration code used on license plates for the German city of Duisburg.
  • D. DU
    DU is an automated underwriting system developed by Fannie Mae that evaluates mortgage loan applications and assesses borrower credit risk.
  • E. DU
    DU is the commonly used abbreviation for the University of Dhaka, a leading public research university in Bangladesh.
  • 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_69d87f1f5bd08190bd01cac0d5b9d2ef completed April 10, 2026, 4:39 a.m.
NER Named-entity recognition batch_69e22711e4fc8190bf7a9f0c59b7889f completed April 17, 2026, 12:26 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0007932f088190b6c20913cfb932f4 completed May 10, 2026, 4:20 a.m.
NEDg Description generation batch_6a0009d6e7288190907075f5ee72f3ad completed May 10, 2026, 4:30 a.m.
NED2 Entity disambiguation (via description) batch_6a000ad7a72481909a74643d8c0c9b5a completed May 10, 2026, 4:34 a.m.
Created at: April 10, 2026, 5:03 a.m.