Triple

T1695009
Position Surface form Disambiguated ID Type / Status
Subject Krefeld E36636 entity
Predicate vehicleRegistrationCode P1173 FINISHED
Object KR
KR is the vehicle registration code used on license plates for the German city of Krefeld.
 E191562 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: KR | Statement: [Krefeld, vehicleRegistrationCode, KR]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: KR
Context triple: [Krefeld, vehicleRegistrationCode, KR]
  • A. KL
    KL is the two-letter IATA airline code assigned to KLM Royal Dutch Airlines.
  • B. KI
    KI is the abbreviation for the Karolinska Institute, a renowned Swedish medical university known for its leading research and role in selecting Nobel laureates in Physiology or Medicine.
  • C. SK
    SK is the postcode area covering Stockport and surrounding parts of Greater Manchester and nearby counties in North West England.
  • D. SK
    SK is the vehicle registration code used on license plates for vehicles registered in Skopje, the capital city of North Macedonia.
  • E. KT
    KT is a UK postcode area covering Kingston upon Thames and surrounding parts of southwest London and north Surrey.
  • 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: KR
Triple: [Krefeld, vehicleRegistrationCode, KR]
Generated description
KR is the vehicle registration code used on license plates for the German city of Krefeld.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: KR
Target entity description: KR is the vehicle registration code used on license plates for the German city of Krefeld.
  • A. KL
    KL is the two-letter IATA airline code assigned to KLM Royal Dutch Airlines.
  • B. KI
    KI is the abbreviation for the Karolinska Institute, a renowned Swedish medical university known for its leading research and role in selecting Nobel laureates in Physiology or Medicine.
  • C. SK
    SK is the postcode area covering Stockport and surrounding parts of Greater Manchester and nearby counties in North West England.
  • D. SK
    SK is the vehicle registration code used on license plates for vehicles registered in Skopje, the capital city of North Macedonia.
  • E. KT
    KT is a UK postcode area covering Kingston upon Thames and surrounding parts of southwest London and north Surrey.
  • 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_69a886163dec8190859c514232a37a05 completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69aa62b3b8908190afc3f9e4a384684f completed March 6, 2026, 5:14 a.m.
NED1 Entity disambiguation (via context triple) batch_69ad7998e1108190aa7430cd4ef887d9 completed March 8, 2026, 1:28 p.m.
NEDg Description generation batch_69ad7a224d248190b0d1a7f70b76c164 completed March 8, 2026, 1:31 p.m.
NED2 Entity disambiguation (via description) batch_69ad7b4b4a208190966fa07a6f0d626e completed March 8, 2026, 1:36 p.m.
Created at: March 4, 2026, 7:30 p.m.