Triple

T16369039
Position Surface form Disambiguated ID Type / Status
Subject Courtney series E397514 entity
Predicate publisher P29 FINISHED
Object Pan Books E12977 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: Pan Books | Statement: [Courtney series, publisher, Pan Books]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Pan Books
Context triple: [Courtney series, publisher, Pan Books]
  • A. Pan Books chosen
    Pan Books is a British publishing imprint known for producing popular fiction and classic titles, including major science fiction works.
  • B. Pocket Books
    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.
  • C. Wave Books
    Wave Books is an independent American poetry press known for publishing innovative contemporary poetry and hybrid literary works.
  • D. Nation Books
    Nation Books is a progressive, politically focused publishing imprint known for releasing works on current affairs, social justice, and investigative journalism.
  • E. Piatkus
    Piatkus is a UK-based publishing imprint known for its commercial fiction and non-fiction titles, particularly in romance, crime, and personal development.
  • 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_69d87f2778dc8190aa95c7572db127e6 completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e2ff4021e88190ad093bab74cf82a4 completed April 18, 2026, 3:49 a.m.
NED1 Entity disambiguation (via context triple) batch_6a002dc29f088190ba5d69ff3c12a251 completed May 10, 2026, 7:03 a.m.
Created at: April 10, 2026, 5:08 a.m.