Triple

T2599479
Position Surface form Disambiguated ID Type / Status
Subject André Schiffrin E58307 entity
Predicate employer P7 FINISHED
Object Pantheon Books E7019 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: Pantheon Books | Statement: [André Schiffrin, employer, Pantheon Books]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Pantheon Books
Context triple: [André Schiffrin, employer, Pantheon Books]
  • A. Pantheon Books chosen
    Pantheon Books is an American publishing imprint known for releasing influential works in politics, history, and critical theory.
  • B. Metropolitan Books
    Metropolitan Books is an American publishing imprint known for releasing influential and often politically engaged nonfiction works by prominent intellectuals and public thinkers.
  • C. The Viking Press
    The Viking Press is an American publishing company known for releasing influential literary works by prominent authors throughout the 20th century.
  • D. Signet Books
    Signet Books is an American paperback publishing imprint known for releasing popular fiction and genre titles, including works by major authors such as Stephen King.
  • E. Arrow Books
    Arrow Books is a British publishing imprint of Cornerstone, part of Penguin Random House UK, known for releasing popular commercial fiction and non-fiction 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_69ab4ac14040819098b13f4a27d5c8ff completed March 6, 2026, 9:44 p.m.
NER Named-entity recognition batch_69abd457564c819080d8c8818c02545a completed March 7, 2026, 7:31 a.m.
NED1 Entity disambiguation (via context triple) batch_69af83cfdd6081908cdeb21243e73dda completed March 10, 2026, 2:37 a.m.
Created at: March 6, 2026, 9:49 p.m.