Triple

T23295662
Position Surface form Disambiguated ID Type / Status
Subject Reba E590161 entity
Predicate executiveProducer P7225 FINISHED
Object Mindy Schultheis 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: Mindy Schultheis | Statement: [Reba, executiveProducer, Mindy Schultheis]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mindy Schultheis
Context triple: [Reba, executiveProducer, Mindy Schultheis]
  • A. Mindy Schultheis chosen
    Mindy Schultheis is a television producer known for her work on various comedy series, including serving as an executive producer on "The President Show."
  • B. Mindy Sterling
    Mindy Sterling is an American actress and comedian best known for her role as the villainous Frau Farbissina in the Austin Powers film series.
  • C. Julie Beckman
    Julie Beckman is an American architect best known for co-designing the National 9/11 Pentagon Memorial in Arlington, Virginia.
  • D. Melinda Kinnaman
    Melinda Kinnaman is an American-Swedish actress known for her work in Swedish film, television, and theatre, including her breakthrough role in the film "My Life as a Dog."
  • E. Melinda Fuller
    Melinda Fuller is a co-founder of WET Design, a prominent water feature design firm known for creating innovative fountains and aquatic installations worldwide.
  • 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_69e25d1af9d88190a0b9b5e8fa608618 completed April 17, 2026, 4:17 p.m.
NER Named-entity recognition batch_69f196cec9e88190b83cfd53a6455e0f completed April 29, 2026, 5:27 a.m.
Created at: April 17, 2026, 5:03 p.m.