Triple

T11273011
Position Surface form Disambiguated ID Type / Status
Subject Cologne Government Region E266859 entity
Predicate hasVehicleRegistrationCode P1173 FINISHED
Object HS
HS is the vehicle registration code used for the district of Heinsberg in the Cologne Government Region of Germany.
 E916229 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: HS | Statement: [Cologne Government Region, hasVehicleRegistrationCode, HS]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: HS
Context triple: [Cologne Government Region, hasVehicleRegistrationCode, HS]
  • A. HS
    HS is an internationally standardized system of names and numbers used to classify traded products for customs and statistical purposes.
  • B. HS
    HS is the postcode area covering the Outer Hebrides (Western Isles) of Scotland.
  • C. SHS
    SHS is the abbreviation commonly used for the Florida State Highway System, the network of state-maintained roads in Florida.
  • D. SHS
    SHS is the commonly used abbreviation for the Shanghai Sharks, a professional basketball team based in Shanghai, China.
  • E. HSC
    HSC is the abbreviation for the Harmonized System Committee, the international body responsible for overseeing and updating the Harmonized Commodity Description and Coding System used in global trade.
  • 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: HS
Triple: [Cologne Government Region, hasVehicleRegistrationCode, HS]
Generated description
HS is the vehicle registration code used for the district of Heinsberg in the Cologne Government Region of Germany.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: HS
Target entity description: HS is the vehicle registration code used for the district of Heinsberg in the Cologne Government Region of Germany.
  • A. HS
    HS is an internationally standardized system of names and numbers used to classify traded products for customs and statistical purposes.
  • B. HS
    HS is the postcode area covering the Outer Hebrides (Western Isles) of Scotland.
  • C. SHS
    SHS is the abbreviation commonly used for the Florida State Highway System, the network of state-maintained roads in Florida.
  • D. SHS
    SHS is the commonly used abbreviation for the Shanghai Sharks, a professional basketball team based in Shanghai, China.
  • E. HSC
    HSC is the abbreviation for the Harmonized System Committee, the international body responsible for overseeing and updating the Harmonized Commodity Description and Coding System used in global trade.
  • 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_69d6aac8c2f48190ad0596f1f89f0470 completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7e965c9048190804ebb48f0a4817b completed April 9, 2026, 6:01 p.m.
NED1 Entity disambiguation (via context triple) batch_69e4f43633948190b86f5603ac50ec47 completed April 19, 2026, 3:26 p.m.
NEDg Description generation batch_69e4f9596e1081908e7b319f77453438 completed April 19, 2026, 3:48 p.m.
NED2 Entity disambiguation (via description) batch_69e4ff5881b8819080f9662a0c2d486d completed April 19, 2026, 4:14 p.m.
Created at: April 8, 2026, 9:31 p.m.