Triple

T19489559
Position Surface form Disambiguated ID Type / Status
Subject Monica Dutton E487610 entity
Predicate portrayedBy P1507 FINISHED
Object Kelsey Asbille 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: Kelsey Asbille | Statement: [Monica Dutton, portrayedBy, Kelsey Asbille]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kelsey Asbille
Context triple: [Monica Dutton, portrayedBy, Kelsey Asbille]
  • A. Kelsey Asbille chosen
    Kelsey Asbille is an American actress known for her roles in television series such as Yellowstone and Teen Wolf, as well as films like Wind River.
  • B. Kelsey Peters
    Kelsey Peters is a driven and ambitious young publishing executive and one of the central protagonists on the television series "Younger."
  • C. Kaitlyn Robrock
    Kaitlyn Robrock is an American voice actress best known for portraying iconic animated characters, including serving as the current voice of Minnie Mouse for Disney.
  • D. Kelsey Burrell
    Kelsey Burrell is known as the child of the Jamaican-American reggae fusion singer and rapper Shaggy.
  • E. Kaylee Hottle
    Kaylee Hottle is a young American actress best known for her breakout role in the MonsterVerse film franchise, where she portrays Jia, a deaf orphan who communicates with King Kong.
  • 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_69d8e8d924388190b847cb15bb3d0aff completed April 10, 2026, 12:11 p.m.
NER Named-entity recognition batch_69e6348ad4088190b530f47efca90165 completed April 20, 2026, 2:13 p.m.
Created at: April 10, 2026, 1:39 p.m.