Triple

T14124406
Position Surface form Disambiguated ID Type / Status
Subject Judy Greer E339989 entity
Predicate name P16 FINISHED
Object Judy Greer E339989 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: Judy Greer | Statement: [Judy Greer, name, Judy Greer]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Judy Greer
Context triple: [Judy Greer, name, Judy Greer]
  • A. Judy Greer chosen
    Judy Greer is an American actress known for her versatile supporting roles in film and television, including appearances in major franchises like the Marvel Cinematic Universe.
  • B. Michaela Watkins
    Michaela Watkins is an American actress and comedian known for her work on "Saturday Night Live" and in numerous television comedies and films.
  • C. Amanda Peet
    Amanda Peet is an American actress known for her work in films like "The Whole Nine Yards" and television series such as "Studio 60 on the Sunset Strip" and "Togetherness."
  • D. Melissa Hudson
    Melissa Hudson is known as the daughter of Stanley Hudson, a character from the American television series "The Office."
  • E. Kathryn Hahn
    Kathryn Hahn is an American actress and comedian known for her versatile roles in film and television, including prominent work in comedies and voice acting.
  • 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_69d81c6a95b481909e39111e0c1f31ee completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de6096976481909dc79066c5165a50 completed April 14, 2026, 3:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69fdf06cddcc81909a1ba268f667dc1d completed May 8, 2026, 2:17 p.m.
Created at: April 9, 2026, 10:22 p.m.