Triple

T23100889
Position Surface form Disambiguated ID Type / Status
Subject Cold and the Crackle E576021 entity
Predicate hasContributor P4244 FINISHED
Object Kylie Tennant 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: Kylie Tennant | Statement: [Cold and the Crackle, hasContributor, Kylie Tennant]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kylie Tennant
Context triple: [Cold and the Crackle, hasContributor, Kylie Tennant]
  • A. Kylie Tennant chosen
    Kylie Tennant was an Australian novelist and playwright known for her socially conscious depictions of working-class life during the Great Depression.
  • B. Emma Tennant
    Emma Tennant was a British novelist known for her experimental, often fantastical fiction and for reimagining classic literary works.
  • C. Leanne Welham
    Leanne Welham is a British film and television director known for her work on acclaimed dramas including the series "The Trial of Christine Keeler."
  • D. Hayley Roberts
    Hayley Roberts is a Welsh former shop assistant and model best known for being married to actor and singer David Hasselhoff.
  • E. Jennifer Ann Agutter
    Jennifer Ann Agutter is an English actress best known for her roles in films such as "The Railway Children," "Walkabout," and "An American Werewolf in London," as well as in the TV series "Call the Midwife."
  • 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_69e245c060b48190a9bd61a47a16db17 completed April 17, 2026, 2:37 p.m.
NER Named-entity recognition batch_69f18de8c5b4819095cddf989cade60d completed April 29, 2026, 4:49 a.m.
Created at: April 17, 2026, 3:58 p.m.