Triple

T6953807
Position Surface form Disambiguated ID Type / Status
Subject Star Trek novels E161191 entity
Predicate publisher P29 FINISHED
Object Pocket Books E24368 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: Pocket Books | Statement: [Star Trek novels, publisher, Pocket Books]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Pocket Books
Context triple: [Star Trek novels, publisher, Pocket Books]
  • A. Pocket Books chosen
    Pocket Books is a long-running American mass-market paperback publisher known for popular fiction and non-fiction titles, operating as an imprint of Simon & Schuster.
  • B. Perseus Books Group
    Perseus Books Group is an American publishing company known for its diverse portfolio of imprints and distribution services for independent publishers.
  • C. Forge Books
    Forge Books is an American publishing imprint known for releasing a wide range of commercial fiction, including thrillers, mysteries, and general-interest novels, under the broader Tor/Forge publishing group.
  • D. Simon & Schuster
    Simon & Schuster is a major American publishing company known for producing a wide range of bestselling fiction and nonfiction books.
  • E. HarperCollins
    HarperCollins is a major global publishing company known for producing a wide range of fiction, non-fiction, and educational books.
  • 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_69c68852a9a0819097797e31d492e273 completed March 27, 2026, 1:38 p.m.
NER Named-entity recognition batch_69c6dacca12481908942ba793a104cc3 completed March 27, 2026, 7:30 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7587ee1b08190b9f53ab7df4a4a58 completed March 28, 2026, 4:26 a.m.
Created at: March 27, 2026, 2:29 p.m.