Triple

T21159862
Position Surface form Disambiguated ID Type / Status
Subject Emil Jannings E521410 entity
Predicate workedWith P398 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, workedWith, Marlene Dietrich]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Marlene Dietrich
Context triple: [Emil Jannings, workedWith, Marlene Dietrich]
  • A. Marlene Dietrich chosen
    Marlene Dietrich was a German-American actress and singer renowned for her iconic film roles, distinctive voice, and androgynous, glamorous persona in classic Hollywood cinema.
  • B. Cyd Charisse
    Cyd Charisse was an American dancer and actress renowned for her dazzling, technically precise performances in classic Hollywood musicals of the 1940s and 1950s.
  • C. Rita Hayworth
    Rita Hayworth was a celebrated American film actress and dancer of Hollywood’s Golden Age, famed for her glamorous screen presence and iconic roles in 1940s musicals and dramas.
  • D. Carole Landis
    Carole Landis was an American film actress and World War II pin-up star known for her glamorous screen presence in 1940s Hollywood.
  • E. Eva Gardner
    Eva Gardner is an American rock bassist best known for her work with bands such as The Mars Volta and for touring with major artists across a variety of genres.
  • 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_69e0b50d1ea481909c07e63c3ead9316 completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e7252f70888190b8e6109cc4099ecc completed April 21, 2026, 7:20 a.m.
Created at: April 16, 2026, 2:59 p.m.