Triple

T23044135
Position Surface form Disambiguated ID Type / Status
Subject Alex Reiger E573826 entity
Predicate createdBy P806 FINISHED
Object Stan Daniels 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: Stan Daniels | Statement: [Alex Reiger, createdBy, Stan Daniels]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Stan Daniels
Context triple: [Alex Reiger, createdBy, Stan Daniels]
  • A. Stan Daniels chosen
    Stan Daniels was a Canadian-born television writer, producer, and director best known for his work on classic sitcoms such as "The Mary Tyler Moore Show" and "Taxi."
  • B. Bruce Daniels
    Bruce Daniels is a computer scientist and game developer best known for co-founding the pioneering interactive fiction company Infocom.
  • C. Mel Daniels
    Mel Daniels was an American professional basketball center best known as a dominant force in the ABA, where he won multiple MVP awards and championships with the Indiana Pacers.
  • D. Dan Dugmore
    Dan Dugmore is an American session musician and steel guitarist known for his work with prominent country and rock artists.
  • E. Phil Lumpkin
    Phil Lumpkin was an American professional basketball player and later a high school basketball coach, best known for his time in the NBA and his successful coaching career in Washington state.
  • 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_69e245b9c11481909d06c872214d21af completed April 17, 2026, 2:37 p.m.
NER Named-entity recognition batch_69f18517083c8190a0850da5440e0a73 completed April 29, 2026, 4:12 a.m.
Created at: April 17, 2026, 3:54 p.m.