Triple

T3281662
Position Surface form Disambiguated ID Type / Status
Subject White Noise E68884 entity
Predicate publisherImprint P2763 FINISHED
Object Viking Penguin E36370 NE FINISHED

How this triple was built (2 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: Viking Penguin | Statement: [White Noise, publisherImprint, Viking Penguin]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Viking Penguin
Context triple: [White Noise, publisherImprint, Viking Penguin]
  • A. Puffin Books
    Puffin Books is a prominent children’s book imprint known for publishing classic and contemporary literature for young readers worldwide.
  • B. Penguin Books chosen
    Penguin Books is a major British publishing house known for its influential paperback editions and wide range of literary and non-fiction titles.
  • C. Grosset & Dunlap
    Grosset & Dunlap is a major American publishing company best known for producing popular mass-market books, including classic children's series and notable political memoirs.
  • D. Razorbill
    Razorbill is a young adult and middle-grade fiction imprint of Penguin Random House known for publishing popular and bestselling titles for teen and preteen readers.
  • E. Macmillan Publishers
    Macmillan Publishers is a major global publishing company known for its wide range of academic, educational, and trade books and imprints.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69ad859c463481909ca4be267336c290 completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adb032d76c81909c568a4e56d12ce9 completed March 8, 2026, 5:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69b2e85528c88190b1e98c680baf3fa8 completed March 12, 2026, 4:22 p.m.
Created at: March 8, 2026, 3:10 p.m.