Triple

T5742669
Position Surface form Disambiguated ID Type / Status
Subject Paula Hawkins E126652 entity
Predicate name P16 FINISHED
Object Paula Hawkins E126652 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: Paula Hawkins | Statement: [Paula Hawkins, name, Paula Hawkins]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Paula Hawkins
Context triple: [Paula Hawkins, name, Paula Hawkins]
  • A. Paula Hawkins chosen
    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.
  • B. Val McDermid
    Val McDermid is a Scottish crime writer renowned for her psychological thrillers and influential contributions to contemporary crime fiction.
  • C. Kate Morton
    Kate Morton is an Australian bestselling novelist known for her atmospheric historical mysteries such as "The Forgotten Garden" and "The House at Riverton."
  • D. Lisa Gardner
    Lisa Gardner is an American author best known for her bestselling crime and psychological thriller novels, including the Detective D.D. Warren and FBI Profiler series.
  • E. Dina Meyer
    Dina Meyer is an American actress best known for her roles in science fiction and horror films and television series, including the Saw franchise and Birds of Prey.
  • 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_69c0083179548190b384b0bf3c08ca4d completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c025852a2c819080521e5b98c00bdc completed March 22, 2026, 5:23 p.m.
NED1 Entity disambiguation (via context triple) batch_69c07e2196e08190a38e1c6871e71acd completed March 22, 2026, 11:41 p.m.
Created at: March 22, 2026, 3:48 p.m.