Triple

T9539123
Position Surface form Disambiguated ID Type / Status
Subject Beatrice Durham E230100 entity
Predicate name P16 FINISHED
Object Beatrice Durham E230100 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: Beatrice Durham | Statement: [Beatrice Durham, name, Beatrice Durham]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Beatrice Durham
Context triple: [Beatrice Durham, name, Beatrice Durham]
  • A. Beatrice Durham chosen
    Beatrice Durham was the wife of pioneering British geneticist William Bateson and a supportive figure in his personal and scientific life.
  • B. Beatrice Taylor
    Beatrice Taylor is the beloved, nurturing aunt character from "The Andy Griffith Show," best known for her role as Aunt Bee in the fictional town of Mayberry.
  • C. Beatrice Pearson
    Beatrice Pearson was an American film actress best known for her leading role in the 1948 film noir "Force of Evil."
  • D. Beatrice Dawson
    Beatrice Dawson was a British costume designer known for her work on mid-20th-century films, earning multiple Academy Award nominations for her period and character costumes.
  • E. Beatrice Straight
    Beatrice Straight was an American actress best known for her Academy Award–winning performance in "Network" and her role in the horror film "Poltergeist."
  • 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_69ca847b1b3081908f72bc932c17cc41 completed March 30, 2026, 2:11 p.m.
NER Named-entity recognition batch_69cd98e4df6c8190a4d1160c42daa45f completed April 1, 2026, 10:15 p.m.
NED1 Entity disambiguation (via context triple) batch_69d161355e2c819099c8e6b974f97608 completed April 4, 2026, 7:06 p.m.
Created at: March 30, 2026, 8:01 p.m.