Triple

T31400545
Position Surface form Disambiguated ID Type / Status
Subject Emil Jannings as Professor Immanuel Rath E800984 entity
Predicate LolaLolaPortrayedBy P1507 FINISHED
Object Marlene Dietrich 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: Marlene Dietrich | Statement: [Emil Jannings as Professor Immanuel Rath, LolaLolaPortrayedBy, Marlene Dietrich]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: LolaLolaPortrayedBy
Context triple: [Emil Jannings as Professor Immanuel Rath, LolaLolaPortrayedBy, Marlene Dietrich]
  • A. portrayedBy chosen
    Indicates that one entity serves as the actor or performer who represents or plays the role of another entity in a work or medium.
  • B. fiancéePortrayedBy
    Indicates that a character’s fiancée is depicted or played by a specific actor or performer.
  • C. portrayedByAlsoKnownFor
    Indicates that an entity is portrayed by a person who is also notably known for another specific role or work.
  • D. surrogateMotherFigurePortrayedBy
    Indicates that one entity is depicted or characterized as a surrogate mother figure to another entity through the performance or portrayal by a specific actor or creator.
  • E. youngerVersionPortrayedBy
    Indicates that one person portrays a younger version of another person, typically in a film, television show, or similar narrative work.
  • 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_69f224ea9998819086ae2e4f4f4091c8 completed April 29, 2026, 3:34 p.m.
NER Named-entity recognition batch_69f6a5f71b2c8190aade8a83f465be0c completed May 3, 2026, 1:33 a.m.
PD Predicate disambiguation batch_69f69fe66df08190958558d63ee623d9 completed May 3, 2026, 1:07 a.m.
Created at: April 29, 2026, 9:19 p.m.