Triple

T12216265
Position Surface form Disambiguated ID Type / Status
Subject Catching the Wolf of Wall Street E291092 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: [Catching the Wolf of Wall Street, publisher, HarperCollins]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: HarperCollins
Context triple: [Catching the Wolf of Wall Street, 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_69d6ab65923081909acfc61b7a612233 completed April 8, 2026, 7:24 p.m.
NER Named-entity recognition batch_69d91c9419d48190b0037fe8edc681c4 completed April 10, 2026, 3:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69f61e46d588819086bfde1b544cab82 completed May 2, 2026, 3:54 p.m.
Created at: April 8, 2026, 9:51 p.m.