Triple

T4737901
Position Surface form Disambiguated ID Type / Status
Subject Celia Johnson E105169 entity
Predicate name P16 FINISHED
Object Celia Johnson E105169 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: Celia Johnson | Statement: [Celia Johnson, name, Celia Johnson]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Celia Johnson
Context triple: [Celia Johnson, name, Celia Johnson]
  • A. Celia Johnson chosen
    Celia Johnson was a distinguished English actress best known for her nuanced, understated performances in classic British films such as "Brief Encounter."
  • B. Flora Robson
    Flora Robson was a distinguished British actress known for her powerful character roles in both stage and film, often portraying strong, authoritative women.
  • C. Anna Massey
    Anna Massey was an acclaimed English actress known for her nuanced performances in film, television, and theatre, including notable roles in psychological dramas and literary adaptations.
  • 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. Margaret Lockwood
    Margaret Lockwood was a popular British film and stage actress best known for her leading roles in 1930s and 1940s classics, particularly in thrillers and melodramas.
  • 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_69bd43ee52048190b81a4f066534ffb3 completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd64844b7081909c9d36e4b461379e completed March 20, 2026, 3:15 p.m.
NED1 Entity disambiguation (via context triple) batch_69be5c8e7c74819080b7a5d3995954dd completed March 21, 2026, 8:53 a.m.
Created at: March 20, 2026, 1:19 p.m.