Triple

T14847427
Position Surface form Disambiguated ID Type / Status
Subject Clive Swift E349133 entity
Predicate workedWith P398 FINISHED
Object Patricia Routledge E1157617 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: Patricia Routledge | Statement: [Clive Swift, workedWith, Patricia Routledge]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Patricia Routledge
Context triple: [Clive Swift, workedWith, Patricia Routledge]
  • A. Patricia Routledge chosen
    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."
  • B. Lesley Garrett
    Lesley Garrett is an English soprano and media personality known for her operatic performances and popular classical crossover work.
  • C. Penelope Wilton
    Penelope Wilton is an English actress known for her acclaimed work in film, television, and theatre, including roles in "Downton Abbey" and "The Best Exotic Marigold Hotel."
  • D. Louise Plowright
    Louise Plowright was a British actress known for her work in television and musical theatre, including notable roles in West End productions.
  • 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 (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_69d822ec69008190a9232caa68836872 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69ded29236dc8190b7d3a37d09f9fb21 completed April 14, 2026, 11:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69ff453e3d3081909f6b6e8b67a824ac completed May 9, 2026, 2:31 p.m.
Created at: April 10, 2026, 1:53 a.m.