Triple

T4560076
Position Surface form Disambiguated ID Type / Status
Subject I, Tonya E120570 entity
Predicate mainCharacter P1183 FINISHED
Object LaVona Golden E179120 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: LaVona Golden | Statement: [I, Tonya, mainCharacter, LaVona Golden]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: LaVona Golden
Context triple: [I, Tonya, mainCharacter, LaVona Golden]
  • A. LaVona Golden chosen
    LaVona Golden is the abrasive, abusive mother of figure skater Tonya Harding, depicted as a central antagonist in the film "I, Tonya."
  • B. Myrna Smith
    Myrna Smith was an American soul and gospel singer best known as a member of the vocal group The Sweet Inspirations, who frequently recorded and toured with artists like Elvis Presley and Aretha Franklin.
  • C. Verna Felton
    Verna Felton was an American character actress and voice performer best known for her memorable roles in classic Disney animated films.
  • D. Gloria Foster
    Gloria Foster was an American actress best known for her acclaimed stage work and for portraying the Oracle in the first two films of The Matrix trilogy.
  • E. Elaine Baker
    Elaine Baker is known as the wife of acclaimed special makeup effects artist and filmmaker Rick Baker.
  • 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_69bd4636f1648190a701445c2fcd9c17 completed March 20, 2026, 1:05 p.m.
NER Named-entity recognition batch_69bd582b871c8190be0b70c76d639000 completed March 20, 2026, 2:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69bdc593eaf881908a9043366230b391 completed March 20, 2026, 10:09 p.m.
Created at: March 20, 2026, 1:09 p.m.