Triple

T11394237
Position Surface form Disambiguated ID Type / Status
Subject The Saga of Jenny E269924 entity
Predicate characterAssociatedWith P63755 FINISHED
Object Liza Elliott E312789 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: Liza Elliott | Statement: [The Saga of Jenny, characterAssociatedWith, Liza Elliott]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Liza Elliott
Context triple: [The Saga of Jenny, characterAssociatedWith, Liza Elliott]
  • A. Liza Elliott chosen
    Liza Elliott is the conflicted, high-powered fashion magazine editor whose psychoanalytic journey drives the plot of the musical "Lady in the Dark."
  • B. Liza Marshall
    Liza Marshall is a British film and television producer known for her work on projects such as "Before I Go to Sleep" and "Temple."
  • C. Liza Todd
    Liza Todd is an American sculptor and the daughter of actress Elizabeth Taylor and producer Mike Todd.
  • D. Liz Rose
    Liz Rose is an American country music songwriter best known for her frequent collaborations with Taylor Swift on several of Swift’s early hit songs.
  • E. Liza Johnson
    Liza Johnson is an American film director and screenwriter known for her character-driven independent films and the historical comedy-drama "Elvis & Nixon."
  • 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_69d6aacdbc6c8190af6dc3d5f5d22836 completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d80018a58c81908b80dc9abd18d650 completed April 9, 2026, 7:38 p.m.
NED1 Entity disambiguation (via context triple) batch_69f457b970b88190869cb0b80aca5c4a completed May 1, 2026, 7:35 a.m.
Created at: April 8, 2026, 9:34 p.m.