Triple

T1062723
Position Surface form Disambiguated ID Type / Status
Subject Babes in Arms E22942 entity
Predicate castMember P1668 FINISHED
Object June Preisser E265603 NE 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: June Preisser | Statement: [Babes in Arms, castMember, June Preisser]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: June Preisser
Context triple: [Babes in Arms, castMember, June Preisser]
  • A. June Preisser chosen
    June Preisser was an American film actress and dancer best known for her energetic supporting roles in 1930s and 1940s Hollywood musicals, often playing peppy, acrobatic teenagers.
  • B. Roberta Seidman
    Roberta Seidman was the wife of American actor John Garfield, a prominent film star of the 1930s and 1940s.
  • C. Jane Rosenthal
    Jane Rosenthal is an American film producer and co-founder of Tribeca Productions and the Tribeca Film Festival, known for her long-time collaboration with Robert De Niro on numerous high-profile films.
  • D. Rose Schlossberg
    Rose Schlossberg is an American actress, comedian, and web series creator, and the eldest grandchild of former U.S. President John F. Kennedy.
  • E. Ann Rosener
    Ann Rosener was an American photographer best known for her documentary images of home-front life and industry during World War II, particularly through her work for U.S. government agencies.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

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_69a493dada0481909c43649f9843ea91 completed March 1, 2026, 7:30 p.m.
NER Named-entity recognition batch_69a4b8f68a54819084326d87c3498252 completed March 1, 2026, 10:08 p.m.
NED1 Entity disambiguation (via context triple) batch_69af1731ebe481908ffd1a670ae86286 completed March 9, 2026, 6:53 p.m.
Created at: March 1, 2026, 7:42 p.m.