Triple

T20592339
Position Surface form Disambiguated ID Type / Status
Subject Melissa Gilbert E505960 entity
Predicate relative P37 FINISHED
Object Sara Gilbert 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: Sara Gilbert | Statement: [Melissa Gilbert, relative, Sara Gilbert]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sara Gilbert
Context triple: [Melissa Gilbert, relative, Sara Gilbert]
  • A. Sara Gilbert chosen
    Sara Gilbert is an American actress and producer best known for her role as Darlene Conner on the sitcom "Roseanne" and as a creator and former co-host of the talk show "The Talk."
  • B. Deborah Norville
    Deborah Norville is an American television journalist and author best known as the longtime anchor of the syndicated newsmagazine program Inside Edition.
  • C. Carey Wilson
    Carey Wilson was an American screenwriter and film producer active during Hollywood's early studio era, known for his work on numerous MGM and RKO pictures.
  • D. Liz Mullally
    Liz Mullally is a musician best known for her past role as a member of the American alternative rock band Blue October.
  • E. Phyllis Smith
    Phyllis Smith is an American actress best known for playing the soft-spoken saleswoman Phyllis Vance on the U.S. version of the television series "The Office."
  • 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_69e0b4ba6ae88190af871e1f9522c704 completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e6a97d63cc8190853e052d5930470d completed April 20, 2026, 10:32 p.m.
Created at: April 16, 2026, 11:40 a.m.