Triple

T17640337
Position Surface form Disambiguated ID Type / Status
Subject Trifling Women E429206 entity
Predicate starring P1507 FINISHED
Object Barbara La Marr 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: Barbara La Marr | Statement: [Trifling Women, starring, Barbara La Marr]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Barbara La Marr
Context triple: [Trifling Women, starring, Barbara La Marr]
  • A. Barbara La Marr chosen
    Barbara La Marr was a popular American silent film actress and screenwriter of the early 1920s, often billed as "The Girl Who Is Too Beautiful."
  • B. Anna Lea Merritt
    Anna Lea Merritt was an American-born British painter of the late 19th and early 20th centuries, best known for her allegorical and religious works and as one of the first women to have a painting purchased for the British national collection.
  • C. Veronica Lake
    Veronica Lake was a popular American film actress of the 1940s, famed for her roles in film noir and her iconic peek-a-boo hairstyle.
  • D. Florence Lawrence
    Florence Lawrence was a pioneering early film actress often regarded as the first movie star to be publicly named and promoted.
  • E. Kay Francis
    Kay Francis was a prominent American film actress of the 1930s, known for her sophisticated screen presence and leading roles in numerous pre-Code and early sound-era Hollywood dramas.
  • 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_69d889e2c2608190b762e76d9b2262f1 completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e46de50bf481909e938613b38f0202 completed April 19, 2026, 5:53 a.m.
Created at: April 10, 2026, 6:02 a.m.