Triple

T10200400
Position Surface form Disambiguated ID Type / Status
Subject Cuxhaven E238867 entity
Predicate vehicleRegistrationCode P1173 FINISHED
Object CUX
CUX is the vehicle registration code used on license plates for vehicles registered in the Cuxhaven district of Germany.
 E847329 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: CUX | Statement: [Cuxhaven, vehicleRegistrationCode, CUX]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: CUX
Context triple: [Cuxhaven, vehicleRegistrationCode, CUX]
  • A. CUZ
    CUZ is the IATA airport code for Alejandro Velasco Astete International Airport serving Cusco, Peru.
  • B. CUMEX
    CUMEX is a consortium of high-quality Mexican universities focused on promoting academic excellence, research, and institutional improvement in higher education.
  • C. CAX
    CAX is the three-letter IATA airport code for Carlisle Lake District Airport in Cumbria, England.
  • D. CUN
    CUN is the IATA airport code for Cancún International Airport, a major gateway for international tourism to Mexico’s Caribbean coast.
  • E. CXA
    CXA is the ICAO airline designator used to identify XiamenAir in international aviation operations and communications.
  • 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: CUX
Triple: [Cuxhaven, vehicleRegistrationCode, CUX]
Generated description
CUX is the vehicle registration code used on license plates for vehicles registered in the Cuxhaven district of Germany.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: CUX
Target entity description: CUX is the vehicle registration code used on license plates for vehicles registered in the Cuxhaven district of Germany.
  • A. CUZ
    CUZ is the IATA airport code for Alejandro Velasco Astete International Airport serving Cusco, Peru.
  • B. CUMEX
    CUMEX is a consortium of high-quality Mexican universities focused on promoting academic excellence, research, and institutional improvement in higher education.
  • C. CAX
    CAX is the three-letter IATA airport code for Carlisle Lake District Airport in Cumbria, England.
  • D. CUN
    CUN is the IATA airport code for Cancún International Airport, a major gateway for international tourism to Mexico’s Caribbean coast.
  • E. CXA
    CXA is the ICAO airline designator used to identify XiamenAir in international aviation operations and communications.
  • 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_69ca84e1ea088190b38162e43d4cfa8f completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cdee3f3bac8190a63a81edffe7cda7 completed April 2, 2026, 4:19 a.m.
NED1 Entity disambiguation (via context triple) batch_69d317f40f0c8190a3d966c934cc20f7 completed April 6, 2026, 2:18 a.m.
NEDg Description generation batch_69d3188886908190ba0a5539ce942980 completed April 6, 2026, 2:20 a.m.
NED2 Entity disambiguation (via description) batch_69d31c4fb8288190bbc6b3d4a79dafb1 completed April 6, 2026, 2:37 a.m.
Created at: March 30, 2026, 9:14 p.m.