Triple

T2273298
Position Surface form Disambiguated ID Type / Status
Subject Bantam Books E50710 entity
Predicate parentCompany P254 FINISHED
Object Penguin Random House E36737 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: Penguin Random House | Statement: [Bantam Books, parentCompany, Penguin Random House]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Penguin Random House
Context triple: [Bantam Books, parentCompany, Penguin Random House]
  • A. Penguin Random House chosen
    Penguin Random House is a major global trade book publisher known for its extensive catalog of fiction and nonfiction titles across numerous imprints.
  • B. Random House
    Random House is a major American book publishing company known for releasing a wide range of influential fiction and nonfiction titles.
  • C. HarperCollins
    HarperCollins is a major global publishing company known for producing a wide range of fiction, non-fiction, and educational books.
  • D. Simon & Schuster
    Simon & Schuster is a major American publishing company known for producing a wide range of bestselling fiction and nonfiction books.
  • E. Random House Studio
    Random House Studio is a media production division associated with the major publishing company Random House, focused on developing and adapting content for film, television, and other entertainment platforms.
  • 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_69a88b05910c8190a9a2b1ff230c85f9 completed March 4, 2026, 7:41 p.m.
NER Named-entity recognition batch_69abc1ea6cc88190982527774223127f completed March 7, 2026, 6:12 a.m.
NED1 Entity disambiguation (via context triple) batch_69b44ec039e881909660350b98d79ba1 completed March 13, 2026, 5:52 p.m.
Created at: March 4, 2026, 7:48 p.m.