Triple

T18125726
Position Surface form Disambiguated ID Type / Status
Subject Paterson E433869 entity
Predicate hasNotableBearer P458 FINISHED
Object Katherine Paterson NE NERFINISHED

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: Katherine Paterson | Statement: [Paterson, hasNotableBearer, Katherine Paterson]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Katherine Paterson
Context triple: [Paterson, hasNotableBearer, Katherine Paterson]
  • A. Katherine Paterson chosen
    Katherine Paterson is an acclaimed American author of children's and young adult literature, best known for novels such as "Bridge to Terabithia" and "Jacob Have I Loved."
  • B. Natalie Babbitt
    Natalie Babbitt was an American author and illustrator of children’s books, best known for her classic fantasy novel "Tuck Everlasting."
  • C. Wendelin Van Draanen
    Wendelin Van Draanen is an American author best known for her young adult and children’s novels, including the popular book "Flipped."
  • D. Margaret Chodos-Irvine
    Margaret Chodos-Irvine is an American illustrator and printmaker known for her distinctive, textured artwork in children’s books.
  • E. Deborah Hopkinson
    Deborah Hopkinson is an American author best known for her historical fiction and nonfiction books for children and young adults, often highlighting social justice and lesser-known figures from history.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8b909e8cc81908df4cc2b8ea6d11f completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e4ddee1efc8190b04324b98de5c9d0 completed April 19, 2026, 1:51 p.m.
Created at: April 10, 2026, 10:29 a.m.