Triple

T10971955
Position Surface form Disambiguated ID Type / Status
Subject Anne Hartnett E259260 entity
Predicate name P16 FINISHED
Object Anne Hartnett E259260 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: Anne Hartnett | Statement: [Anne Hartnett, name, Anne Hartnett]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Anne Hartnett
Context triple: [Anne Hartnett, name, Anne Hartnett]
  • A. Anne Hartnett chosen
    Anne Hartnett is an individual notable enough to be recognized as a prominent bearer of the surname Hartnett.
  • B. Anne Howe
    Anne Howe was the first wife of British comic actor Peter Sellers, with whom she had two children before their divorce.
  • C. Anne Howe
    Anne Howe is a fictional character from the comic strip "Palooka," likely serving as part of the supporting cast around the title figure.
  • D. Lydia Davis
    Lydia Davis is an American writer renowned for her extremely short, experimental short stories and her acclaimed translations of French literature.
  • E. Ann Beattie
    Ann Beattie is an American author renowned for her incisive short stories and novels depicting contemporary life and relationships, often associated with the minimalist literary movement.
  • 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_69d6aa895f4c8190887a15460ef622f4 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d7719b5edc81908c1019f81e78bd2e completed April 9, 2026, 9:30 a.m.
NED1 Entity disambiguation (via context triple) batch_69e2d790df108190b4a3a6fece372778 completed April 18, 2026, 1 a.m.
Created at: April 8, 2026, 9:24 p.m.