Triple

T1677054
Position Surface form Disambiguated ID Type / Status
Subject Heckler & Koch E36253 entity
Predicate abbreviation P43 FINISHED
Object HK
HK is a renowned German defense manufacturer best known for designing and producing small arms such as pistols, rifles, and submachine guns used by military and law enforcement worldwide.
 E189859 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: [Heckler & Koch, abbreviation, HK]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: HK
Context triple: [Heckler & Koch, abbreviation, HK]
  • A. HK
    HK is the vehicle registration code used for the Czech city of Hradec Králové.
  • B. HK
    HK is the vehicle registration code used on license plates for vehicles registered in Ahlden, a municipality in Lower Saxony, Germany.
  • C. Kowloon
    Kowloon is a densely populated urban area of Hong Kong known for its vibrant street life, markets, and skyline facing Victoria Harbour.
  • D. 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.
  • E. Hakka
    Hakka is a Sinitic language spoken primarily by the Hakka people across southern China and various overseas Chinese communities.
  • 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: [Heckler & Koch, abbreviation, HK]
Generated description
HK is a renowned German defense manufacturer best known for designing and producing small arms such as pistols, rifles, and submachine guns used by military and law enforcement worldwide.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: HK
Target entity description: HK is a renowned German defense manufacturer best known for designing and producing small arms such as pistols, rifles, and submachine guns used by military and law enforcement worldwide.
  • A. HK
    HK is the vehicle registration code used for the Czech city of Hradec Králové.
  • B. HK
    HK is the vehicle registration code used on license plates for vehicles registered in Ahlden, a municipality in Lower Saxony, Germany.
  • C. Kowloon
    Kowloon is a densely populated urban area of Hong Kong known for its vibrant street life, markets, and skyline facing Victoria Harbour.
  • D. 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.
  • E. Hakka
    Hakka is a Sinitic language spoken primarily by the Hakka people across southern China and various overseas Chinese communities.
  • 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_69a886139ed081909af0940aa9313512 completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69aa625e4cd0819083825b41196f902d completed March 6, 2026, 5:13 a.m.
NED1 Entity disambiguation (via context triple) batch_69ad71b7c2608190bce1dc7469da4c45 completed March 8, 2026, 12:55 p.m.
NEDg Description generation batch_69ad72deafcc8190a2aef87277c5d731 completed March 8, 2026, 1 p.m.
NED2 Entity disambiguation (via description) batch_69ad734440ac81909cbcf1c02fd4bc66 completed March 8, 2026, 1:01 p.m.
Created at: March 4, 2026, 7:29 p.m.