Triple

T19223760
Position Surface form Disambiguated ID Type / Status
Subject Michael Moritz E480683 entity
Predicate authorOf P4244 FINISHED
Object The Little Kingdom 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: The Little Kingdom | Statement: [Michael Moritz, authorOf, The Little Kingdom]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: The Little Kingdom
Context triple: [Michael Moritz, authorOf, The Little Kingdom]
  • A. The Little Kingdom chosen
    The Little Kingdom is a nonfiction book by Michael Moritz that chronicles the early history and rise of Apple Computer and its founders.
  • B. The Little Ruler
    The Little Ruler is a notable literary work by influential Iranian poet Ahmad Shamlu, reflecting his modernist style and socially conscious themes.
  • C. The King Who Rained
    The King Who Rained is a humorous children's picture book that plays on English homophones and literal interpretations of common phrases, written and illustrated by actor-author Fred Gwynne.
  • D. Die Kinder
    Die Kinder is a 1990 British television drama miniseries about political intrigue and personal danger surrounding a couple searching for their missing children in Europe.
  • E. Ein Kind
    Ein Kind is an autobiographical work by Austrian writer Thomas Bernhard that recounts his bleak and formative childhood experiences.
  • 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_69d8e8ccb8f48190ad420098e74fb1db completed April 10, 2026, 12:10 p.m.
NER Named-entity recognition batch_69e5fa95743481909314fd14e2c3d189 completed April 20, 2026, 10:06 a.m.
Created at: April 10, 2026, 1:24 p.m.