Triple

T3906583
Position Surface form Disambiguated ID Type / Status
Subject The Lake House E87215 entity
Predicate author P4 FINISHED
Object Kate Morton E87215 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: Kate Morton | Statement: [The Lake House, author, Kate Morton]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kate Morton
Context triple: [The Lake House, author, Kate Morton]
  • A. Kate Morton chosen
    Kate Morton is an Australian bestselling novelist known for her atmospheric historical mysteries such as "The Forgotten Garden" and "The House at Riverton."
  • B. 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.
  • C. 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.
  • D. Mary Higgins Clark
    Mary Higgins Clark was a bestselling American author renowned for her suspenseful mystery and thriller novels, often featuring strong female protagonists.
  • E. Lucinda Riley
    Lucinda Riley was a bestselling Irish author best known for her multi-volume historical fiction series "The Seven Sisters," which achieved international acclaim.
  • 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_69aed9424514819086e9c58adde6652d completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aeed1290e48190aaf2d8b2a7be707a completed March 9, 2026, 3:53 p.m.
NED1 Entity disambiguation (via context triple) batch_69b55614ffa48190b15a1c2ec20638f2 completed March 14, 2026, 12:35 p.m.
Created at: March 9, 2026, 3:22 p.m.