Triple

T24886635
Position Surface form Disambiguated ID Type / Status
Subject To Norma Jeane with Love, Jimmie E622870 entity
Predicate alternateNameOfMainSubject P157439 FINISHED
Object Marilyn Monroe 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: Marilyn Monroe | Statement: [To Norma Jeane with Love, Jimmie, alternateNameOfMainSubject, Marilyn Monroe]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: alternateNameOfMainSubject
Context triple: [To Norma Jeane with Love, Jimmie, alternateNameOfMainSubject, Marilyn Monroe]
  • A. hasSecondarySubject
    Indicates that an entity is associated with an additional, non-primary subject in a given context or relationship.
  • B. secondaryDiscipline
    Indicates that an entity has an additional, subordinate field of study or area of specialization associated with it, distinct from its primary discipline.
  • C. annexASubject
    Indicates that one entity formally incorporates another entity as a subordinate or dependent part under its control.
  • D. secondaryTo
    Indicates that one condition, event, or factor occurs as a consequence of, or is caused by, another primary condition, event, or factor.
  • E. hasPrimarySubject
    Indicates that an entity is the main or principal subject associated with another entity or resource.
  • F. None of above. chosen

Provenance (4 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_69e2fac4aa848190b3446a3922cec150 completed April 18, 2026, 3:30 a.m.
NER Named-entity recognition batch_69f43043512481909501a3979cac9947 completed May 1, 2026, 4:46 a.m.
PD Predicate disambiguation batch_69f420fd375c81908ea4a4e60b76ee8f completed May 1, 2026, 3:41 a.m.
PDg Predicate description generation batch_69f4303fad6c8190844f069164f0904d completed May 1, 2026, 4:46 a.m.
Created at: April 18, 2026, 5:25 a.m.