Triple

T4580498
Position Surface form Disambiguated ID Type / Status
Subject Oil and Honey E101841 entity
Predicate publisher P29 FINISHED
Object Times Books E1321 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: Times Books | Statement: [Oil and Honey, publisher, Times Books]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Times Books
Context triple: [Oil and Honey, publisher, Times Books]
  • A. Times Books chosen
    Times Books is a publishing imprint known for producing nonfiction works, particularly in the fields of history, politics, and current affairs.
  • B. Nation Books
    Nation Books is a progressive, politically focused publishing imprint known for releasing works on current affairs, social justice, and investigative journalism.
  • C. Pan Books
    Pan Books is a British publishing imprint known for producing popular fiction and classic titles, including major science fiction works.
  • D. Books Division
    The Books Division is the publishing arm of the University of Chicago Press responsible for producing and distributing its scholarly and general-interest books.
  • E. Gallery Books
    Gallery Books is a publishing imprint known for releasing a wide range of commercial fiction and nonfiction titles, including bestsellers and works by popular contemporary authors.
  • 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_69bd43d4ce208190b53158c882b222e3 completed March 20, 2026, 12:55 p.m.
NER Named-entity recognition batch_69bd58e534708190a1ba9c5a29b3774d completed March 20, 2026, 2:25 p.m.
NED1 Entity disambiguation (via context triple) batch_69bdd3f532dc81909b6c464defada832 completed March 20, 2026, 11:10 p.m.
Created at: March 20, 2026, 1:10 p.m.