Triple

T20819807
Position Surface form Disambiguated ID Type / Status
Subject Legion (2010 film) E512542 entity
Predicate stars P1956 FINISHED
Object Willa Holland 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: Willa Holland | Statement: [Legion (2010 film), stars, Willa Holland]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Willa Holland
Context triple: [Legion (2010 film), stars, Willa Holland]
  • A. Willa Holland chosen
    Willa Holland is an American actress and model best known for her roles on the television series "The O.C." and "Arrow."
  • B. Madeleine Stowe
    Madeleine Stowe is an American actress best known for her film roles in the 1990s, including "The Last of the Mohicans" and "12 Monkeys," and later for her acclaimed television work.
  • C. Rebecca Herbst
    Rebecca Herbst is an American actress best known for her long-running role as nurse Elizabeth Webber on the soap opera "General Hospital."
  • D. Deborah Anne Mazar
    Deborah Anne Mazar is an American actress known for her sharp-tongued, tough-girl roles in film and television, including notable appearances in "Goodfellas," "Entourage," and "Younger."
  • E. Kathrine Narducci
    Kathrine Narducci is an American actress best known for her roles in Italian-American crime dramas, including prominent parts in films and television series such as The Sopranos.
  • 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_69e0b4ce39108190a6e8e5df4f1c8dc5 completed April 16, 2026, 10:07 a.m.
NER Named-entity recognition batch_69e6c2f6a65481909a0df78616e185e4 completed April 21, 2026, 12:21 a.m.
Created at: April 16, 2026, 12:41 p.m.