Triple

T21602636
Position Surface form Disambiguated ID Type / Status
Subject Sergeant Joe Swanson E533085 entity
Predicate child P120 FINISHED
Object Susie Swanson 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: Susie Swanson | Statement: [Sergeant Joe Swanson, child, Susie Swanson]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Susie Swanson
Context triple: [Sergeant Joe Swanson, child, Susie Swanson]
  • A. Susie Swanson chosen
    Susie Swanson is a minor character on the animated TV show "Family Guy," known as the infant daughter of Joe and Bonnie Swanson.
  • B. Susie Bannion
    Susie Bannion is the young American dancer who becomes entangled with a coven of witches at a prestigious Berlin dance academy in the 2018 horror film "Suspiria."
  • C. Susie Conklin
    Susie Conklin is a British television producer and writer known for her work on period dramas such as the adaptation of Elizabeth Gaskell’s "Cranford."
  • D. Susie Waggoner
    Susie Waggoner is a key fictional character in the crime film "Miami Blues," known for her involvement with the film’s charismatic but dangerous antihero.
  • E. Susie Sprague
    Susie Sprague is an American model and actress best known for her work in glamour modeling and for her high-profile marriage to actor Corey Feldman.
  • 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_69e0c46364608190a337dc8720dc2a35 completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69ef17e31c80819090fdd63b5c103acb completed April 27, 2026, 8:01 a.m.
Created at: April 16, 2026, 6:33 p.m.