Triple

T377662
Position Surface form Disambiguated ID Type / Status
Subject Florence Pugh E8606 entity
Predicate name P16 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: [Florence Pugh, name, Florence Pugh]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Florence Pugh
Context triple: [Florence Pugh, name, 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. Cailee Spaeny
    Cailee Spaeny is an American actress known for her breakout role in the science fiction film "Pacific Rim: Uprising" and subsequent performances in both film and television.
  • C. Carmen Ejogo
    Carmen Ejogo is a British actress and singer known for her versatile film and television roles, including her acclaimed portrayal of Coretta Scott King in the historical drama "Selma."
  • D. Olivia Thirlby
    Olivia Thirlby is an American actress known for her roles in films such as "Juno," "Dredd," and various independent and mainstream productions.
  • E. Jane Wyman
    Jane Wyman was an American actress and Academy Award winner best known for her film and television work in the mid-20th century.
  • 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_69a2e7f47dd08190a4e294ccbbe46cd4 completed Feb. 28, 2026, 1:04 p.m.
NER Named-entity recognition batch_69a2ec1804108190a1e94526b71289ea completed Feb. 28, 2026, 1:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69a3fe92911881908ee7f88d5c628ec9 completed March 1, 2026, 8:53 a.m.
Created at: Feb. 28, 2026, 1:08 p.m.