Triple

T19312468
Position Surface form Disambiguated ID Type / Status
Subject Stefania LaVie Owen E483004 entity
Predicate hasWorkedWith P9615 FINISHED
Object Chloë Sevigny 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: Chloë Sevigny | Statement: [Stefania LaVie Owen, hasWorkedWith, Chloë Sevigny]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Chloë Sevigny
Context triple: [Stefania LaVie Owen, hasWorkedWith, Chloë Sevigny]
  • A. Chloë Sevigny chosen
    Chloë Sevigny is an American actress and fashion icon known for her work in independent films and her distinctive, avant-garde style.
  • B. 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."
  • C. Elizabeth Perkins
    Elizabeth Perkins is an American actress known for her versatile film and television roles, including work in both live-action and animated projects.
  • D. Alison Lohman
    Alison Lohman is an American actress known for her roles in films such as Big Fish, White Oleander, and Drag Me to Hell.
  • E. Samantha Morton
    Samantha Morton is an acclaimed English actress and director known for her intense, emotionally rich performances in independent films and major productions alike.
  • 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_69d8e8d04d5c8190baa816986f2b1d1e completed April 10, 2026, 12:10 p.m.
NER Named-entity recognition batch_69e604ce5de081909811c49f56ba94bb completed April 20, 2026, 10:49 a.m.
Created at: April 10, 2026, 1:32 p.m.