Triple

T5368876
Position Surface form Disambiguated ID Type / Status
Subject Nicolas Cage E108795 entity
Predicate spouse P13 FINISHED
Object Patricia Arquette E67684 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: Patricia Arquette | Statement: [Nicolas Cage, spouse, Patricia Arquette]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Patricia Arquette
Context triple: [Nicolas Cage, spouse, Patricia Arquette]
  • A. Patricia Arquette chosen
    Patricia Arquette is an American actress acclaimed for her versatile film and television roles, including award-winning performances in projects like "Medium" and "Boyhood."
  • B. Jacki Weaver
    Jacki Weaver is an Australian actress acclaimed for her work in film, television, and theatre, including her Oscar-nominated performance in "Silver Linings Playbook."
  • C. Melissa Leo
    Melissa Leo is an American actress acclaimed for her powerful character roles in film and television, including her Oscar-winning performance in "The Fighter."
  • D. Gina Gershon
    Gina Gershon is an American actress known for her versatile roles in film, television, and theater, including standout performances in movies like "Bound" and "Showgirls."
  • E. Maria Bello
    Maria Bello is an American actress known for her versatile roles in film and television, including performances in projects like "A History of Violence," "ER," and "NCIS."
  • 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_69bd440c77948190aad2a5f39b7b80f5 completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd86856f688190a34ab93619bae134 completed March 20, 2026, 5:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69bf292c4d1c819088f7b977ac212688 completed March 21, 2026, 11:26 p.m.
Created at: March 20, 2026, 2:02 p.m.