Triple

T22644454
Position Surface form Disambiguated ID Type / Status
Subject Kozienice E558919 entity
Predicate vehicleRegistrationCode P1173 FINISHED
Object WKZ
WKZ is the Polish vehicle registration code assigned to cars registered in the town of Kozienice.
 E1547102 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: WKZ | Statement: [Kozienice, vehicleRegistrationCode, WKZ]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: WKZ
Context triple: [Kozienice, vehicleRegistrationCode, WKZ]
  • A. WZ
    WZ is the IATA airline designator assigned to Red Wings Airlines, a Russian passenger carrier.
  • B. KZ
    KZ is the two-letter ISO 3166-1 alpha-2 country code assigned to Kazakhstan for international standardization and identification.
  • C. ZWZ
    ZWZ was the Polish underground military organization formed during World War II that later evolved into the Home Army (Armia Krajowa), the main resistance force against Nazi occupation.
  • D. WZE
    WZE is a Polish defense electronics company specializing in the development, production, and modernization of military electronic systems and equipment.
  • E. ZWKL
    ZWKL is the ICAO airport code for Korla Airport in Xinjiang, China.
  • 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: WKZ
Triple: [Kozienice, vehicleRegistrationCode, WKZ]
Generated description
WKZ is the Polish vehicle registration code assigned to cars registered in the town of Kozienice.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: WKZ
Target entity description: WKZ is the Polish vehicle registration code assigned to cars registered in the town of Kozienice.
  • A. WZ
    WZ is the IATA airline designator assigned to Red Wings Airlines, a Russian passenger carrier.
  • B. KZ
    KZ is the two-letter ISO 3166-1 alpha-2 country code assigned to Kazakhstan for international standardization and identification.
  • C. ZWZ
    ZWZ was the Polish underground military organization formed during World War II that later evolved into the Home Army (Armia Krajowa), the main resistance force against Nazi occupation.
  • D. WZE
    WZE is a Polish defense electronics company specializing in the development, production, and modernization of military electronic systems and equipment.
  • E. ZWKL
    ZWKL is the ICAO airport code for Korla Airport in Xinjiang, China.
  • 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_69e24547f7fc819086e2c4ba3b979657 completed April 17, 2026, 2:35 p.m.
NER Named-entity recognition batch_69f170366ac881909e9d1dd2e7cf7a25 completed April 29, 2026, 2:43 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0b58626738819085ce5ad6683cb1fe completed May 18, 2026, 6:20 p.m.
NEDg Description generation batch_6a0b6f5d272c8190bf66fa372fb2bb7d completed May 18, 2026, 7:58 p.m.
NED2 Entity disambiguation (via description) batch_6a0b7072e43c8190ad8f8d09f61d3f7b completed May 18, 2026, 8:02 p.m.
Created at: April 17, 2026, 3:05 p.m.