Triple

T1435802
Position Surface form Disambiguated ID Type / Status
Subject Ahlden E30556 entity
Predicate vehicleRegistrationCode P1173 FINISHED
Object HK
HK is the vehicle registration code used on license plates for vehicles registered in Ahlden, a municipality in Lower Saxony, Germany.
E163585 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: HK | Statement: [Ahlden, vehicleRegistrationCode, HK]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: HK
Context triple: [Ahlden, vehicleRegistrationCode, HK]
  • A. HK
    HK is the vehicle registration code used for the Czech city of Hradec Králové.
  • B. Kowloon
    Kowloon is a densely populated urban area of Hong Kong known for its vibrant street life, markets, and skyline facing Victoria Harbour.
  • C. Hong Kong, China
    Hong Kong, China is a major global financial and trading hub and a Special Administrative Region of China located on the southern coast of the country.
  • D. Hakka
    Hakka is a Sinitic language spoken primarily by the Hakka people across southern China and various overseas Chinese communities.
  • E. MHK
    MHK is the post-nominal abbreviation used by elected members of the House of Keys, the lower branch of the Isle of Man's parliament.
  • 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: HK
Triple: [Ahlden, vehicleRegistrationCode, HK]
Generated description
HK is the vehicle registration code used on license plates for vehicles registered in Ahlden, a municipality in Lower Saxony, Germany.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: HK
Target entity description: HK is the vehicle registration code used on license plates for vehicles registered in Ahlden, a municipality in Lower Saxony, Germany.
  • A. HK
    HK is the vehicle registration code used for the Czech city of Hradec Králové.
  • B. Kowloon
    Kowloon is a densely populated urban area of Hong Kong known for its vibrant street life, markets, and skyline facing Victoria Harbour.
  • C. Hong Kong, China
    Hong Kong, China is a major global financial and trading hub and a Special Administrative Region of China located on the southern coast of the country.
  • D. Hakka
    Hakka is a Sinitic language spoken primarily by the Hakka people across southern China and various overseas Chinese communities.
  • E. MHK
    MHK is the post-nominal abbreviation used by elected members of the House of Keys, the lower branch of the Isle of Man's parliament.
  • 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_69a498fc69ec8190b61722bd4b67c4d2 completed March 1, 2026, 7:52 p.m.
NER Named-entity recognition batch_69a4c50250b88190a0fcf3e0cbba0b1a completed March 1, 2026, 11 p.m.
NED1 Entity disambiguation (via context triple) batch_69ad017084908190a81a784ae4a53c21 completed March 8, 2026, 4:56 a.m.
NEDg Description generation batch_69ad0259651c8190890e45c1786a9a50 completed March 8, 2026, 5 a.m.
NED2 Entity disambiguation (via description) batch_69ad03018aa4819090020ba89a11d0cd completed March 8, 2026, 5:02 a.m.
Created at: March 1, 2026, 8 p.m.