Triple

T23172286
Position Surface form Disambiguated ID Type / Status
Subject Madame Sousatzka E578890 entity
Predicate starring P1507 FINISHED
Object Peggy Ashcroft 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: Peggy Ashcroft | Statement: [Madame Sousatzka, starring, Peggy Ashcroft]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Peggy Ashcroft
Context triple: [Madame Sousatzka, starring, Peggy Ashcroft]
  • A. Peggy Ashcroft chosen
    Peggy Ashcroft was a distinguished English stage and film actress renowned for her Shakespearean performances and her long, influential career in British theatre.
  • B. Peggy Arliss
    Peggy Arliss was the wife of British screenwriter and film director Leslie Arliss, associated with the mid-20th-century British film industry.
  • C. Edith Lesley
    Edith Lesley was an American educator and founder of the teacher-training institution that evolved into Lesley University in Cambridge, Massachusetts.
  • D. Billie Whitelaw
    Billie Whitelaw was an acclaimed English actress renowned for her intense stage and screen performances, particularly in the plays of Samuel Beckett.
  • E. Phyllis Fraser
    Phyllis Fraser was an American actress-turned-publishing executive and children's book editor who co-founded Beginner Books and played a key role in popularizing early readers like those by Dr. Seuss.
  • 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_69e245fd2a388190b814c0dfa15f7148 completed April 17, 2026, 2:38 p.m.
NER Named-entity recognition batch_69f18f30ce148190a6de928c8213399e completed April 29, 2026, 4:55 a.m.
Created at: April 17, 2026, 4:04 p.m.