Triple

T10949031
Position Surface form Disambiguated ID Type / Status
Subject Kutno E258676 entity
Predicate hasCarPlatesCode P26915 FINISHED
Object EKU
EKU is the vehicle registration plate code assigned to the town of Kutno in central Poland.
 E895743 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: EKU | Statement: [Kutno, hasCarPlatesCode, EKU]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: EKU
Context triple: [Kutno, hasCarPlatesCode, EKU]
  • A. EKU
    EKU is a public university located in Richmond, Kentucky, known for its programs in education, criminal justice, and liberal arts.
  • B. UAK
    UAK was the temporary currency code used for the Ukrainian karbovanets, a transitional currency of Ukraine in the early 1990s before the introduction of the hryvnia.
  • C. UoK
    UoK is the commonly used abbreviation for the University of Khartoum, a leading public university in Sudan.
  • D. ESU
    ESU is a specialized police emergency response unit that handles high-risk situations such as tactical operations, rescues, and hazardous incidents.
  • E. ESU
    ESU is a public university in Emporia, Kansas, known for its programs in education, business, and liberal arts.
  • 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: EKU
Triple: [Kutno, hasCarPlatesCode, EKU]
Generated description
EKU is the vehicle registration plate code assigned to the town of Kutno in central Poland.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: EKU
Target entity description: EKU is the vehicle registration plate code assigned to the town of Kutno in central Poland.
  • A. EKU
    EKU is a public university located in Richmond, Kentucky, known for its programs in education, criminal justice, and liberal arts.
  • B. UAK
    UAK was the temporary currency code used for the Ukrainian karbovanets, a transitional currency of Ukraine in the early 1990s before the introduction of the hryvnia.
  • C. UoK
    UoK is the commonly used abbreviation for the University of Khartoum, a leading public university in Sudan.
  • D. ESU
    ESU is a specialized police emergency response unit that handles high-risk situations such as tactical operations, rescues, and hazardous incidents.
  • E. ESU
    ESU is a public university in Emporia, Kansas, known for its programs in education, business, and liberal arts.
  • 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_69d6aa88500c819097d7032ca578e74f completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d770ec7028819084f5ce2035a128e4 completed April 9, 2026, 9:27 a.m.
NED1 Entity disambiguation (via context triple) batch_69e23c4a75688190894c83b8964509a6 completed April 17, 2026, 1:57 p.m.
NEDg Description generation batch_69e24542b4f081909c97621f04da8ecc completed April 17, 2026, 2:35 p.m.
NED2 Entity disambiguation (via description) batch_69e248f7f96481909fa6e6cd07891566 completed April 17, 2026, 2:51 p.m.
Created at: April 8, 2026, 9:23 p.m.