Triple

T18707533
Position Surface form Disambiguated ID Type / Status
Subject Barbara Morton E457411 entity
Predicate associatedWithAuthor P2830 FINISHED
Object Patricia Highsmith 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: Patricia Highsmith | Statement: [Barbara Morton, associatedWithAuthor, Patricia Highsmith]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Patricia Highsmith
Context triple: [Barbara Morton, associatedWithAuthor, Patricia Highsmith]
  • A. Patricia Highsmith chosen
    Patricia Highsmith was an American novelist best known for her psychologically complex crime and suspense fiction, including the Ripley series.
  • B. Sally Kellerman
    Sally Kellerman was an American actress and singer best known for her Oscar-nominated role as Major Margaret "Hot Lips" Houlihan in the film MASH.
  • C. Mary Higgins Clark
    Mary Higgins Clark was a bestselling American author renowned for her suspenseful mystery and thriller novels, often featuring strong female protagonists.
  • D. Sue Grafton
    Sue Grafton was an American mystery writer best known for her alphabet-titled Kinsey Millhone detective novels.
  • E. Paula Hawkins
    Paula Hawkins is a British author best known for her psychological thriller novel "The Girl on the Train," which was adapted into the 2016 film of the same name.
  • 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_69d8d392aad081909fe31aa03e6e97d1 completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e567185c648190848ca47498eb56b3 completed April 19, 2026, 11:36 p.m.
Created at: April 10, 2026, 11:50 a.m.