Triple

T16846331
Position Surface form Disambiguated ID Type / Status
Subject Burn E409547 entity
Predicate publisher P29 FINISHED
Object Walker Books E1046043 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: Walker Books | Statement: [Burn, publisher, Walker Books]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Walker Books
Context triple: [Burn, publisher, Walker Books]
  • A. Walker Books chosen
    Walker Books is a British independent children's book publisher renowned for producing acclaimed and innovative picture books, fiction, and non-fiction for young readers.
  • B. Puffin Books
    Puffin Books is a prominent children’s book imprint known for publishing classic and contemporary literature for young readers worldwide.
  • C. Faber Children’s Books
    Faber Children’s Books is the children’s publishing imprint of the independent British publisher Faber and Faber, known for its high-quality and often award-winning books for young readers.
  • D. Egmont Books
    Egmont Books is a British children's publishing company best known for producing popular series such as The Railway Series featuring Thomas the Tank Engine.
  • E. Hayden Books
    Hayden Books was a technical and computer science publishing imprint known for producing influential programming and computing manuals in the late 20th century.
  • 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_69d883952b048190887740a980b712ed completed April 10, 2026, 4:59 a.m.
NER Named-entity recognition batch_69e3b354eaf081908fe6f84a330d7866 completed April 18, 2026, 4:37 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00dbfb781881908f4d56f523e78f7a completed May 10, 2026, 7:26 p.m.
Created at: April 10, 2026, 5:24 a.m.