Triple

T13518121
Position Surface form Disambiguated ID Type / Status
Subject Rudy Steiner E322820 entity
Predicate createdBy P806 FINISHED
Object Markus Zusak E322815 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: Markus Zusak | Statement: [Rudy Steiner, createdBy, Markus Zusak]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Markus Zusak
Context triple: [Rudy Steiner, createdBy, Markus Zusak]
  • A. Markus Zusak chosen
    Markus Zusak is an Australian novelist best known for his internationally acclaimed World War II–set novel "The Book Thief."
  • B. Mark Haddon
    Mark Haddon is a British author best known for his award-winning novel "The Curious Incident of the Dog in the Night-Time," which has been widely acclaimed and adapted for stage and screen.
  • C. Mitchell Burgess
    Mitchell Burgess is an American television writer and producer best known for his work on the acclaimed HBO series *The Sopranos*.
  • D. Yann Martel
    Yann Martel is a Canadian author best known for his philosophical novel "Life of Pi," which achieved international acclaim and widespread popularity.
  • E. Brian Selznick
    Brian Selznick is an American author and illustrator best known for his innovative, cinematic illustrated novels for children, including *The Invention of Hugo Cabret*.
  • 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_69d80766a21881909f21a1b7421d3b8a completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbafa27f048190bed33a98e28c8d09 completed April 12, 2026, 2:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69f79d3afa0c81908733f3fd193d4e0f completed May 3, 2026, 7:08 p.m.
Created at: April 9, 2026, 9:44 p.m.