Triple

T14958490
Position Surface form Disambiguated ID Type / Status
Subject Thelma Harper E372996 entity
Predicate hasRelative P367 FINISHED
Object Sonja Harper E391214 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: Sonja Harper | Statement: [Thelma Harper, hasRelative, Sonja Harper]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sonja Harper
Context triple: [Thelma Harper, hasRelative, Sonja Harper]
  • A. Sonja Harper chosen
    Sonja Harper is a teenage granddaughter in the sitcom "Mama’s Family," known for her rebellious streak and frequent clashes with her sharp-tongued grandmother, Thelma Harper.
  • B. Sonja Hood
    Sonja Hood is an Australian sports administrator who serves as the president of the North Melbourne Football Club in the Australian Football League.
  • C. Paula Harper
    Paula Harper is a fictional character appearing in the narrative work "The Masks."
  • D. Susannah Shipman
    Susannah Shipman is a film producer best known for her work on the Academy Award–winning documentary "Taxi to the Dark Side."
  • E. Elaine Harper
    Elaine Harper is a young minister's daughter and the fiancée of drama critic Mortimer Brewster in the dark comedic play "Arsenic and Old Lace."
  • 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_69d85cca979481908747d2a81eba1cea completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69ded6cd85bc81909040b7ff78f62554 completed April 15, 2026, 12:07 a.m.
NED1 Entity disambiguation (via context triple) batch_69febfd3ebd08190a2b7c70c2ba6deb3 completed May 9, 2026, 5:02 a.m.
Created at: April 10, 2026, 2:40 a.m.