Triple

T11885455
Position Surface form Disambiguated ID Type / Status
Subject Vladek Spiegelman E282768 entity
Predicate hasChild P369 FINISHED
Object Art Spiegelman E276731 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: Art Spiegelman | Statement: [Vladek Spiegelman, hasChild, Art Spiegelman]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Art Spiegelman
Context triple: [Vladek Spiegelman, hasChild, Art Spiegelman]
  • A. Art Spiegelman chosen
    Art Spiegelman is an American cartoonist and editor best known for his Pulitzer Prize–winning graphic novel "Maus," which depicts the Holocaust through anthropomorphic characters.
  • B. Sol Spiegelman
    Sol Spiegelman was an American molecular biologist renowned for his pioneering work on nucleic acid hybridization and the molecular mechanisms of viral replication.
  • C. Vladek Spiegelman
    Vladek Spiegelman is the Holocaust-survivor father whose life story is recounted in Art Spiegelman’s graphic memoir Maus.
  • D. Margo Roth Spiegelman
    Margo Roth Spiegelman is a mysterious, adventurous teenage girl whose disappearance drives the plot and emotional journey of John Green’s novel "Paper Towns."
  • E. Will Eisner
    Will Eisner was a pioneering American cartoonist and graphic novelist, widely regarded as one of the most influential figures in the history of comics and sequential art.
  • 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_69d6ab2a90b08190a4e818821cc93e6d completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d8d3a13370819086386fecb99e4f0b completed April 10, 2026, 10:40 a.m.
NED1 Entity disambiguation (via context triple) batch_69f417da310c8190aa04df2a316a5dd0 completed May 1, 2026, 3:02 a.m.
Created at: April 8, 2026, 9:44 p.m.