Triple

T1699610
Position Surface form Disambiguated ID Type / Status
Subject Penguin Random House E36737 entity
Predicate hasImprint P2763 FINISHED
Object DK
DK is a British illustrated reference publisher best known for its highly visual nonfiction books for children and adults across topics like science, history, travel, and nature.
 E190649 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: DK | Statement: [Penguin Random House, hasImprint, DK]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: DK
Context triple: [Penguin Random House, hasImprint, DK]
  • A. DK
    DK is the ISO 3166-1 alpha-2 country code for Denmark, a Nordic nation in Northern Europe.
  • B. KD
    KD is the widely used nickname of Kevin Durant, an elite NBA scorer and multi-time champion regarded as one of the greatest basketball players of his generation.
  • C. CK
    CK is a 1988 studio album by American singer Chaka Khan that blends R&B, funk, and pop with contemporary production.
  • D. EK
    EK is the commonly used abbreviation for the First Chamber of the Austrian Parliament (Erste Kammer).
  • E. KC
    KC is a common shorthand nickname for Kansas City, Missouri, a major Midwestern U.S. city known for its jazz heritage, barbecue, and sports teams.
  • 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: DK
Triple: [Penguin Random House, hasImprint, DK]
Generated description
DK is a British illustrated reference publisher best known for its highly visual nonfiction books for children and adults across topics like science, history, travel, and nature.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: DK
Target entity description: DK is a British illustrated reference publisher best known for its highly visual nonfiction books for children and adults across topics like science, history, travel, and nature.
  • A. DK
    DK is the ISO 3166-1 alpha-2 country code for Denmark, a Nordic nation in Northern Europe.
  • B. KD
    KD is the widely used nickname of Kevin Durant, an elite NBA scorer and multi-time champion regarded as one of the greatest basketball players of his generation.
  • C. CK
    CK is a 1988 studio album by American singer Chaka Khan that blends R&B, funk, and pop with contemporary production.
  • D. EK
    EK is the commonly used abbreviation for the First Chamber of the Austrian Parliament (Erste Kammer).
  • E. KC
    KC is a common shorthand nickname for Kansas City, Missouri, a major Midwestern U.S. city known for its jazz heritage, barbecue, and sports teams.
  • 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_69a886163dec8190859c514232a37a05 completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69aa62d3c57c81908887844e885062e3 completed March 6, 2026, 5:14 a.m.
NED1 Entity disambiguation (via context triple) batch_69ad799d59a48190b1efb101c2a67e4f completed March 8, 2026, 1:29 p.m.
NEDg Description generation batch_69ad7a12d1048190ade4e1a84638215e completed March 8, 2026, 1:30 p.m.
NED2 Entity disambiguation (via description) batch_69ad7a8fe4d88190beb1e6b8cd778501 completed March 8, 2026, 1:33 p.m.
Created at: March 4, 2026, 7:30 p.m.