Triple

T1614167
Position Surface form Disambiguated ID Type / Status
Subject Arthur Gettleman E34676 entity
Predicate spouseOfPersonBestKnownFor P19181 FINISHED
Object role of Sophia Petrillo on television series "The Golden Girls" LITERAL 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: role of Sophia Petrillo on television series "The Golden Girls" | Statement: [Arthur Gettleman, spouseOfPersonBestKnownFor, role of Sophia Petrillo on television series "The Golden Girls"]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: spouseOfPersonBestKnownFor
Context triple: [Arthur Gettleman, spouseOfPersonBestKnownFor, role of Sophia Petrillo on television series "The Golden Girls"]
  • A. spouseNotableFor chosen
    Indicates that a person's spouse is recognized or distinguished for a particular achievement, role, or characteristic.
  • B. spouseNotableWorkField
    Indicates that the notable work or professional field associated with a person’s spouse is being specified.
  • C. spouseOfHonouree
    Indicates that one person is the spouse (married partner) of the honouree.
  • D. firstWifeOf
    Indicates that one person is the first woman to have been married to another person.
  • E. firstHolderSpouseOf
    Indicates that the first holder in the relation is the spouse (married partner) of the other holder.
  • F. None of above.

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_69a885ffc5ec819091afa325d5f9611c completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69a93fef600c819080fe75c42c8e6dac completed March 5, 2026, 8:33 a.m.
PD Predicate disambiguation batch_69a907c52a548190b648a31ea306dd5b completed March 5, 2026, 4:34 a.m.
Created at: March 4, 2026, 7:28 p.m.