Triple

T17051169
Position Surface form Disambiguated ID Type / Status
Subject Lab Girl E413699 entity
Predicate publisher P29 FINISHED
Object Vintage Books E49810 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: Vintage Books | Statement: [Lab Girl, publisher, Vintage Books]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Vintage Books
Context triple: [Lab Girl, publisher, Vintage Books]
  • A. Vintage Books chosen
    Vintage Books is a prominent publishing imprint known for its wide-ranging catalog of literary fiction, classics, and quality non-fiction titles.
  • B. Vintage Publishing
    Vintage Publishing is a prominent British publishing imprint known for its wide-ranging list of literary fiction, non-fiction, and classic titles.
  • C. Virgin Books
    Virgin Books is a British publishing imprint associated with Richard Branson’s Virgin Group, known for releasing a range of non-fiction, biographies, and entertainment-related titles.
  • D. Modern Classics
    Modern Classics is a renowned Penguin Books imprint that publishes influential 20th- and 21st-century literature in distinctive, curated paperback editions.
  • E. Vintage Stuff
    Vintage Stuff is a comic novel by British satirist Tom Sharpe that parodies English public schools and military adventure stories through the misadventures of an inept young teacher.
  • 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_69d886cde3d481908d4d01ba88ba7eb7 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3daa26e84819098b41ae15618e813 completed April 18, 2026, 7:25 p.m.
NED1 Entity disambiguation (via context triple) batch_6a012341b8e88190a2bee865be5ca1c1 completed May 11, 2026, 12:30 a.m.
Created at: April 10, 2026, 5:34 a.m.