Triple

T8508132
Position Surface form Disambiguated ID Type / Status
Subject David G. Hartwell E201385 entity
Predicate employer P7 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: [David G. Hartwell, employer, HarperCollins]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: HarperCollins
Context triple: [David G. Hartwell, employer, 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_69ca8320e5748190ac2c585a0bba8193 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cbe5df74e8819086b1445cc907e371 completed March 31, 2026, 3:18 p.m.
NED1 Entity disambiguation (via context triple) batch_69ce6cc36a74819082713f53bb6755d7 completed April 2, 2026, 1:18 p.m.
Created at: March 30, 2026, 6:15 p.m.