Triple

T21887397
Position Surface form Disambiguated ID Type / Status
Subject Go Gently: Actionable Steps to Nurture Yourself and the Planet E540441 entity
Predicate author P4 FINISHED
Object Bonnie Wright 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: Bonnie Wright | Statement: [Go Gently: Actionable Steps to Nurture Yourself and the Planet, author, Bonnie Wright]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bonnie Wright
Context triple: [Go Gently: Actionable Steps to Nurture Yourself and the Planet, author, Bonnie Wright]
  • A. Bonnie Wright chosen
    Bonnie Wright is an English actress and filmmaker best known for playing Ginny Weasley in the Harry Potter film series.
  • B. Prunella Scales
    Prunella Scales is an English actress best known for her comic role as Sybil Fawlty in the classic British sitcom "Fawlty Towers."
  • C. Hermione Baddeley
    Hermione Baddeley was an English character actress known for her sharp-tongued, memorable supporting roles in British cinema and later in Hollywood films and television.
  • D. Evanna Lynch
    Evanna Lynch is an Irish actress best known for playing Luna Lovegood in the Harry Potter film series.
  • E. Jane Wenham
    Jane Wenham was a British actress known for her work in mid-20th-century film, television, and theatre.
  • 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_69e0c47a95908190ae3e19b716accb3d completed April 16, 2026, 11:14 a.m.
NER Named-entity recognition batch_69f118ed35948190bbffba2c40029eee completed April 28, 2026, 8:30 p.m.
Created at: April 16, 2026, 7:05 p.m.