Triple

T9938475
Position Surface form Disambiguated ID Type / Status
Subject Kielce E194016 entity
Predicate vehicleRegistrationCode P1173 FINISHED
Object TK
TK is the vehicle registration code assigned to motor vehicles registered in the city of Kielce, Poland.
 E830947 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: TK | Statement: [Kielce, vehicleRegistrationCode, TK]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: TK
Context triple: [Kielce, vehicleRegistrationCode, TK]
  • A. TK
    TK is the two-letter IATA airline designator used to identify Turkish Airlines in global aviation systems.
  • B. KT
    KT is a UK postcode area covering Kingston upon Thames and surrounding parts of southwest London and north Surrey.
  • 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. KT
    KT is the official vehicle registration code used on license plates for vehicles registered in Katsina State, Nigeria.
  • E. Tok
    Tok is a small unincorporated community in eastern Alaska, known as a gateway to the state for travelers on the Alaska Highway.
  • 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: TK
Triple: [Kielce, vehicleRegistrationCode, TK]
Generated description
TK is the vehicle registration code assigned to motor vehicles registered in the city of Kielce, Poland.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: TK
Target entity description: TK is the vehicle registration code assigned to motor vehicles registered in the city of Kielce, Poland.
  • A. TK
    TK is the two-letter IATA airline designator used to identify Turkish Airlines in global aviation systems.
  • B. KT
    KT is a UK postcode area covering Kingston upon Thames and surrounding parts of southwest London and north Surrey.
  • 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. KT
    KT is the official vehicle registration code used on license plates for vehicles registered in Katsina State, Nigeria.
  • E. Tok
    Tok is a small unincorporated community in eastern Alaska, known as a gateway to the state for travelers on the Alaska Highway.
  • 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_69ca82e409348190a393777356b80a2a completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cdb5e64760819094f599f158d32f33 completed April 2, 2026, 12:18 a.m.
NED1 Entity disambiguation (via context triple) batch_69d228f259b081909ce8a90ec1adad0d completed April 5, 2026, 9:18 a.m.
NEDg Description generation batch_69d22a78819481908ccff34730464f19 completed April 5, 2026, 9:25 a.m.
NED2 Entity disambiguation (via description) batch_69d22b0fea588190a4928c361c2367ca completed April 5, 2026, 9:27 a.m.
Created at: March 30, 2026, 8:44 p.m.