Triple

T8451056
Position Surface form Disambiguated ID Type / Status
Subject Blonde (2022 film) E199797 entity
Predicate hasBiographicalBasis P75959 FINISHED
Object life of Marilyn Monroe LITERAL 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: life of Marilyn Monroe | Statement: [Blonde (2022 film), hasBiographicalBasis, life of Marilyn Monroe]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasBiographicalBasis
Context triple: [Blonde (2022 film), hasBiographicalBasis, life of Marilyn Monroe]
  • A. hasBiographicalTheme chosen
    Indicates that something (such as a work, text, or content) centers on or significantly involves biographical subject matter, such as a person’s life, experiences, or personal history.
  • B. hasUncertainBiographicalDetails
    Indicates that the biographical information about an entity is incomplete, ambiguous, or not reliably established.
  • C. hasPartInBiography
    Indicates that a person or entity is featured or plays a role within someone’s biographical account.
  • D. usesBiographicalStructure
    Indicates that one entity employs or is organized according to the biographical structure of another entity (e.g., a work structured around a person’s life story).
  • E. hasAutobiographicalElements
    Indicates that something, such as a work or narrative, contains elements drawn from the creator’s own life or personal experiences.
  • F. None of above.

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_69ca8318231881908fd1bc1c4d45d286 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cbe44815488190a912d63512e19af0 completed March 31, 2026, 3:12 p.m.
PD Predicate disambiguation batch_69cbd0fc634481909842c0a30077bfde completed March 31, 2026, 1:49 p.m.
Created at: March 30, 2026, 6:09 p.m.