Triple

T4028729
Position Surface form Disambiguated ID Type / Status
Subject Just a Minute E83654 entity
Predicate regularPanellist P858 FINISHED
Object Sheila Hancock E22751 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: Sheila Hancock | Statement: [Just a Minute, regularPanellist, Sheila Hancock]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sheila Hancock
Context triple: [Just a Minute, regularPanellist, Sheila Hancock]
  • A. Sheila Hancock chosen
    Sheila Hancock is a British actress and author renowned for her extensive work in theatre, television, and film, as well as her appearances as a television presenter and panelist.
  • B. Lesley Garrett
    Lesley Garrett is an English soprano and media personality known for her operatic performances and popular classical crossover work.
  • C. Shirley Henderson
    Shirley Henderson is a Scottish actress known for her distinctive voice and roles in films such as the Bridget Jones series and the Harry Potter franchise.
  • D. Joanne Whalley
    Joanne Whalley is an English actress known for her film and television roles, including her prominent performance in the fantasy adventure film "Willow."
  • E. Patricia Clarkson
    Patricia Clarkson is an American actress acclaimed for her versatile performances in film, television, and theater, often in complex supporting roles.
  • 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_69aed92e29ac819080f7a98b594fec05 completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69af01994b0c8190b34af36acadad5c6 completed March 9, 2026, 5:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69b589ccd0a48190b98dbe7268df678f completed March 14, 2026, 4:16 p.m.
Created at: March 9, 2026, 3:36 p.m.