Triple

T10676955
Position Surface form Disambiguated ID Type / Status
Subject 8 Million Ways to Die E251644 entity
Predicate starring P1507 FINISHED
Object Rosanna Arquette E340706 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: Rosanna Arquette | Statement: [8 Million Ways to Die, starring, Rosanna Arquette]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Rosanna Arquette
Context triple: [8 Million Ways to Die, starring, Rosanna Arquette]
  • A. Rosanna Arquette chosen
    Rosanna Arquette is an American actress and filmmaker known for her roles in films such as "Desperately Seeking Susan" and "Pulp Fiction."
  • B. Luana Patten
    Luana Patten was an American child actress best known for her early work in Walt Disney films during the 1940s and 1950s.
  • C. Teresa Ganzel
    Teresa Ganzel is an American actress and comedian best known for her frequent appearances on The Tonight Show Starring Johnny Carson and her roles in 1980s comedies and voice acting.
  • D. Donna Peele
    Donna Peele is an American former model best known for her brief mid-1990s marriage to actor Charlie Sheen.
  • E. Teri Garr
    Teri Garr is an American actress known for her versatile performances in films such as "Young Frankenstein," "Close Encounters of the Third Kind," and "Tootsie."
  • 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_69d6aa5b0d2881909584b20efc5877f0 completed April 8, 2026, 7:19 p.m.
NER Named-entity recognition batch_69d6fb9563908190a69cf4bd2c24fd2f completed April 9, 2026, 1:06 a.m.
NED1 Entity disambiguation (via context triple) batch_69e343cd76448190b0583cc15005ac9d completed April 18, 2026, 8:41 a.m.
Created at: April 8, 2026, 9:09 p.m.