Triple

T9010347
Position Surface form Disambiguated ID Type / Status
Subject Landkreis Günzburg E215451 entity
Predicate hasVehicleRegistrationCode P1173 FINISHED
Object GZ
GZ is the vehicle registration code used on license plates for the district of Günzburg in Bavaria, Germany.
 E772662 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: GZ | Statement: [Landkreis Günzburg, hasVehicleRegistrationCode, GZ]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: GZ
Context triple: [Landkreis Günzburg, hasVehicleRegistrationCode, GZ]
  • A. GZT
    GZT is the IATA airport code for Oğuzeli Airport serving Gaziantep in southeastern Turkey.
  • B. GZP
    GZP is the ICAO airline designator assigned to Gazpromavia, the Russian airline owned by the energy company Gazprom.
  • C. GZM
    GZM is a major metropolitan area, often referring to the Upper Silesian–Zagłębie Metropolis in southern Poland, encompassing a large urban and industrial region.
  • D. GZQ
    GZQ is the station code used to identify Guangzhou Railway Station, a major rail transport hub in Guangzhou, China.
  • E. Giez
    Giez is a small municipality in the canton of Vaud in western Switzerland, situated near the town of Grandson and close to Lake Neuchâtel.
  • 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: GZ
Triple: [Landkreis Günzburg, hasVehicleRegistrationCode, GZ]
Generated description
GZ is the vehicle registration code used on license plates for the district of Günzburg in Bavaria, Germany.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: GZ
Target entity description: GZ is the vehicle registration code used on license plates for the district of Günzburg in Bavaria, Germany.
  • A. GZT
    GZT is the IATA airport code for Oğuzeli Airport serving Gaziantep in southeastern Turkey.
  • B. GZP
    GZP is the ICAO airline designator assigned to Gazpromavia, the Russian airline owned by the energy company Gazprom.
  • C. GZM
    GZM is a major metropolitan area, often referring to the Upper Silesian–Zagłębie Metropolis in southern Poland, encompassing a large urban and industrial region.
  • D. GZQ
    GZQ is the station code used to identify Guangzhou Railway Station, a major rail transport hub in Guangzhou, China.
  • E. Giez
    Giez is a small municipality in the canton of Vaud in western Switzerland, situated near the town of Grandson and close to Lake Neuchâtel.
  • 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_69ca83a2bf088190986ee7a8eb90407d completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cc69c1571881908d0b144786b5ee1f completed April 1, 2026, 12:41 a.m.
NED1 Entity disambiguation (via context triple) batch_69cfdb9dca848190952427bb5712081f completed April 3, 2026, 3:24 p.m.
NEDg Description generation batch_69cfdc5b230881908057cc868e44ea44 completed April 3, 2026, 3:27 p.m.
NED2 Entity disambiguation (via description) batch_69cfdcfc28288190b849b3f0216a7e9a completed April 3, 2026, 3:30 p.m.
Created at: March 30, 2026, 7:06 p.m.