Triple

T10890734
Position Surface form Disambiguated ID Type / Status
Subject Katie Silberman E257165 entity
Predicate collaboratedWith P435 FINISHED
Object Florence Pugh E8606 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: Florence Pugh | Statement: [Katie Silberman, collaboratedWith, Florence Pugh]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Florence Pugh
Context triple: [Katie Silberman, collaboratedWith, Florence Pugh]
  • A. Florence Pugh chosen
    Florence Pugh is an English actress acclaimed for her emotionally intense and versatile performances in films such as "Lady Macbeth," "Midsommar," and "Little Women."
  • B. Lucy Boynton
    Lucy Boynton is a British-American actress known for her roles in films such as "Bohemian Rhapsody" and "Sing Street," as well as various television dramas.
  • C. Vanessa Kirby
    Vanessa Kirby is an English actress known for her acclaimed performances in both film and television, including her breakout role as Princess Margaret in the Netflix series "The Crown."
  • D. Maria Riva
    Maria Riva is a German-American actress and author best known as the daughter and biographer of film legend Marlene Dietrich.
  • E. Tamsin Egerton
    Tamsin Egerton is an English actress and model known for roles in films such as "St Trinian's," "Keeping Mum," and "The Look of Love."
  • 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_69d6aa8550c8819095508a2ed9acf3db completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d7520550c4819081296546c8f534f1 completed April 9, 2026, 7:15 a.m.
NED1 Entity disambiguation (via context triple) batch_69e46283f41c8190ac3e1f196c5e4ca0 completed April 19, 2026, 5:05 a.m.
Created at: April 8, 2026, 9:21 p.m.