Triple

T16846332
Position Surface form Disambiguated ID Type / Status
Subject Burn E409547 entity
Predicate publisher P29 FINISHED
Object HarperCollins E65842 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: HarperCollins | Statement: [Burn, publisher, HarperCollins]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: HarperCollins
Context triple: [Burn, publisher, HarperCollins]
  • A. HarperCollins chosen
    HarperCollins is a major global publishing company known for producing a wide range of fiction, non-fiction, and educational books.
  • B. Simon & Schuster
    Simon & Schuster is a major American publishing company known for producing a wide range of bestselling fiction and nonfiction books.
  • C. Penguin Random House
    Penguin Random House is a major global trade book publisher known for its extensive catalog of fiction and nonfiction titles across numerous imprints.
  • D. Macmillan Publishers
    Macmillan Publishers is a major global publishing company known for its wide range of academic, educational, and trade books and imprints.
  • E. Random House
    Random House is a major American book publishing company known for releasing a wide range of influential fiction and nonfiction titles.
  • 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_69d883952b048190887740a980b712ed completed April 10, 2026, 4:59 a.m.
NER Named-entity recognition batch_69e3b354eaf081908fe6f84a330d7866 completed April 18, 2026, 4:37 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00bb1b47648190909eaaf4e1e8e4c3 completed May 10, 2026, 5:06 p.m.
Created at: April 10, 2026, 5:24 a.m.