Triple

T20385162
Position Surface form Disambiguated ID Type / Status
Subject The Three Lives of Thomasina E497939 entity
Predicate portrayedBy P1507 FINISHED
Object Susan Hampshire 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: Susan Hampshire | Statement: [The Three Lives of Thomasina, portrayedBy, Susan Hampshire]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Susan Hampshire
Context triple: [The Three Lives of Thomasina, portrayedBy, Susan Hampshire]
  • A. Susan Hampshire chosen
    Susan Hampshire is an English actress best known for her award-winning performances in British television dramas and period adaptations.
  • B. Patricia Routledge
    Patricia Routledge is an English actress and comedian best known for her acclaimed stage work and for starring as the snobbish Hyacinth Bucket in the sitcom "Keeping Up Appearances."
  • C. Lesley Garrett
    Lesley Garrett is an English soprano and media personality known for her operatic performances and popular classical crossover work.
  • D. Helen Mary Warnock
    Helen Mary Warnock was a prominent British philosopher and educationalist best known for her influential work on ethics, special education, and public policy.
  • E. Frances Barber
    Frances Barber is an English actress known for her extensive work in film, television, and theatre, including roles in productions such as "Film Stars Don’t Die in Liverpool."
  • 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_69e6790a31a4819099b2e6df2bafe547 completed April 20, 2026, 7:05 p.m.
Created at: April 16, 2026, 11:28 a.m.