Triple

T23104288
Position Surface form Disambiguated ID Type / Status
Subject Bolivar Trask E576119 entity
Predicate child P120 FINISHED
Object Tanya Trask 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: Tanya Trask | Statement: [Bolivar Trask, child, Tanya Trask]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tanya Trask
Context triple: [Bolivar Trask, child, Tanya Trask]
  • A. Tanya Trask chosen
    Tanya Trask is a Marvel Comics character associated with the X-Men mythos, known primarily as the time-traveling mutant daughter of Sentinel-creator Bolivar Trask.
  • B. Erika Tymrak
    Erika Tymrak is an American professional soccer midfielder known for her playmaking creativity in the National Women's Soccer League and appearances with the United States women's national team.
  • C. Tanya Reynolds
    Tanya Reynolds is a British actress best known for her role as Lily Iglehart in the Netflix series "Sex Education."
  • D. Tracy Reed
    Tracy Reed was an American actress and model known for her roles in 1960s and 1970s films and television.
  • E. Tracy Ham
    Tracy Ham is a former professional gridiron football quarterback best known for his standout career in the Canadian Football League, where he became one of the league’s premier dual-threat passers in the late 1980s and 1990s.
  • 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_69e245f4af548190898d434a64a1e774 completed April 17, 2026, 2:38 p.m.
NER Named-entity recognition batch_69f18deb702c819099f2e2141706f00e completed April 29, 2026, 4:49 a.m.
Created at: April 17, 2026, 3:58 p.m.