Triple

T20386772
Position Surface form Disambiguated ID Type / Status
Subject Spaced E497979 entity
Predicate characterPortrayedBy P1507 FINISHED
Object Daisy Steiner – Jessica Hynes NE NERFINISHED

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: Daisy Steiner – Jessica Hynes | Statement: [Spaced, characterPortrayedBy, Daisy Steiner – Jessica Hynes]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Daisy Steiner – Jessica Hynes
Context triple: [Spaced, characterPortrayedBy, Daisy Steiner – Jessica Hynes]
  • A. Daisy Steiner chosen
    Daisy Steiner is a quirky, aspiring writer and journalist who serves as one of the two main protagonists in the British sitcom "Spaced."
  • B. Daisy (Love Actually)
    Daisy is Karen and Harry’s young daughter in the film "Love Actually," best known for her role in the school Christmas pageant scene.
  • C. Daisy Mason
    Daisy Mason is a kitchen maid who rises through the ranks in the early 20th-century English estate setting of the television series "Downton Abbey."
  • D. Daisy Danby
    Daisy Danby is a fictional character known primarily as the romantic interest of Ira Wright.
  • E. Daisy Fay
    Daisy Fay is the witty, sharp-tongued Southern girl who narrates Fannie Flagg’s coming-of-age novel "Daisy Fay and the Miracle Man," chronicling her eccentric childhood and growth in mid-20th-century Mississippi.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0b4a71ebc8190b153a36c738730f4 completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e6790bcef481909453d19c846ab420 completed April 20, 2026, 7:05 p.m.
Created at: April 16, 2026, 11:28 a.m.