Triple

T10988193
Position Surface form Disambiguated ID Type / Status
Subject Kitzingen (district) E259684 entity
Predicate vehicleRegistrationCode P1173 FINISHED
Object KT
KT is the vehicle registration code used on license plates for the Kitzingen district in Bavaria, Germany.
 E898335 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: KT | Statement: [Kitzingen (district), vehicleRegistrationCode, KT]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: KT
Context triple: [Kitzingen (district), vehicleRegistrationCode, KT]
  • A. KT
    KT is a UK postcode area covering Kingston upon Thames and surrounding parts of southwest London and north Surrey.
  • B. KT
    KT is the official vehicle registration code used on license plates for vehicles registered in Katsina State, Nigeria.
  • C. KT
    KT is the post-nominal abbreviation for Knight of the Order of the Thistle, one of Scotland’s highest and oldest orders of chivalry.
  • D. TK
    TK is the two-letter IATA airline designator used to identify Turkish Airlines in global aviation systems.
  • E. TK
    TK is the vehicle registration code assigned to motor vehicles registered in the city of Kielce, Poland.
  • 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: KT
Triple: [Kitzingen (district), vehicleRegistrationCode, KT]
Generated description
KT is the vehicle registration code used on license plates for the Kitzingen district in Bavaria, Germany.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: KT
Target entity description: KT is the vehicle registration code used on license plates for the Kitzingen district in Bavaria, Germany.
  • A. KT
    KT is a UK postcode area covering Kingston upon Thames and surrounding parts of southwest London and north Surrey.
  • B. KT
    KT is the official vehicle registration code used on license plates for vehicles registered in Katsina State, Nigeria.
  • C. KT
    KT is the post-nominal abbreviation for Knight of the Order of the Thistle, one of Scotland’s highest and oldest orders of chivalry.
  • D. TK
    TK is the two-letter IATA airline designator used to identify Turkish Airlines in global aviation systems.
  • E. TK
    TK is the vehicle registration code assigned to motor vehicles registered in the city of Kielce, Poland.
  • 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_69d6aa8a6a548190a750f944ccdc8064 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d787b574d08190adec34b814a26437 completed April 9, 2026, 11:04 a.m.
NED1 Entity disambiguation (via context triple) batch_69e344f95ab88190bbce8f0eab0b2713 completed April 18, 2026, 8:46 a.m.
NEDg Description generation batch_69e3556e8b408190a02a1fe194ae5750 completed April 18, 2026, 9:57 a.m.
NED2 Entity disambiguation (via description) batch_69e3591ecd548190b049ce95fe3f86d9 completed April 18, 2026, 10:12 a.m.
Created at: April 8, 2026, 9:24 p.m.