Triple

T3944738
Position Surface form Disambiguated ID Type / Status
Subject Upstairs, Downstairs E92118 entity
Predicate character P662 FINISHED
Object Rose Buck E402622 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: Rose Buck | Statement: [Upstairs, Downstairs, character, Rose Buck]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Rose Buck
Context triple: [Upstairs, Downstairs, character, Rose Buck]
  • A. Rose Buck chosen
    Rose Buck is a central maid and housekeeper character in the British television drama series "Upstairs, Downstairs."
  • B. Bessie Carter
    Bessie Carter is an English actress known for roles in period dramas such as "Howards End" and "Bridgerton."
  • C. Grace Rose
    Grace Rose is a painting by the Victorian English artist Frederic Sandys, known for its richly detailed Pre-Raphaelite style and evocative portrayal of a female subject.
  • D. Antonia Van Drimmelen
    Antonia Van Drimmelen is a film editor known for her work on the political drama film "Charlie Wilson's War."
  • E. Aggie Herring
    Aggie Herring was an American character actress of the silent and early sound film era, known for her supporting roles in numerous Hollywood productions.
  • 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_69aed965502c8190904ebad1203a4ae8 completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aef0d8841081908d2c1de8e5758017 completed March 9, 2026, 4:10 p.m.
NED1 Entity disambiguation (via context triple) batch_69b53ff967a88190b0100dbedb580e4d completed March 14, 2026, 11:01 a.m.
Created at: March 9, 2026, 3:24 p.m.