Triple

T10194249
Position Surface form Disambiguated ID Type / Status
Subject Elizabethtown E238117 entity
Predicate starring P1507 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: [Elizabethtown, starring, Judy Greer]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Judy Greer
Context triple: [Elizabethtown, starring, 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_69ca84de1b208190bf17bb305b002605 completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cdedc7cc748190bceb8f657afcc054 completed April 2, 2026, 4:17 a.m.
NED1 Entity disambiguation (via context triple) batch_69d32aef701c8190a01e632eb4fda1b9 completed April 6, 2026, 3:39 a.m.
Created at: March 30, 2026, 9:13 p.m.