Triple

T13384333
Position Surface form Disambiguated ID Type / Status
Subject Good Girls E319400 entity
Predicate castMember P1668 FINISHED
Object Retta E319407 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: Retta | Statement: [Good Girls, castMember, Retta]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Retta
Context triple: [Good Girls, castMember, Retta]
  • A. Retta chosen
    Retta is an American actress and comedian best known for her roles on the television series "Parks and Recreation" and "Good Girls."
  • B. Lucy DeVito
    Lucy DeVito is an American actress known for her work in film, television, and theater, and as the daughter of actors Danny DeVito and Rhea Perlman.
  • C. Gina Linetti
    Gina Linetti is a hilariously self-absorbed, sharp-tongued civilian administrator known for her bizarre confidence and deadpan humor on the sitcom Brooklyn Nine-Nine.
  • D. Renny
    Renny is a diminutive or short form of the given name René, often used as a familiar or affectionate variant.
  • E. Judi Farr
    Judi Farr was an Australian actress known for her extensive work in theatre, film, and television, including prominent roles in classic Australian TV comedies and dramas.
  • 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_69d806b886bc8190b676e7768b8e01c5 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69dadce80158819082156eaeaeda3bd8 completed April 11, 2026, 11:44 p.m.
NED1 Entity disambiguation (via context triple) batch_69f7306c18d481908ebc8f802e474479 completed May 3, 2026, 11:24 a.m.
Created at: April 9, 2026, 9:33 p.m.