Triple

T13595678
Position Surface form Disambiguated ID Type / Status
Subject Michael McDonald E324811 entity
Predicate associatedAct P37 FINISHED
Object Donald Fagen E495538 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: Donald Fagen | Statement: [Michael McDonald, associatedAct, Donald Fagen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Donald Fagen
Context triple: [Michael McDonald, associatedAct, Donald Fagen]
  • A. Greg Morrisett
    Greg Morrisett is a computer scientist known for his work on programming languages and type systems, particularly in the design of safe and secure systems.
  • B. Mike Garfath
    Mike Garfath is a cinematographer best known for his work on the British neo-noir film "Croupier."
  • C. Walter Becker chosen
    Walter Becker was an American musician, songwriter, and record producer best known as the co-founder, guitarist, and bassist of the jazz-rock band Steely Dan.
  • D. Michael Franks
    Michael Franks is an American jazz and soft rock singer-songwriter known for his smooth vocal style and sophisticated, often witty lyrics.
  • E. Gordon Gano
    Gordon Gano is an American musician best known as the lead singer, guitarist, and primary songwriter for the alternative rock band Violent Femmes.
  • 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_69d80769eaf081909d82f44e484d6113 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbb0590558819080ccc5874a650b1e completed April 12, 2026, 2:46 p.m.
NED1 Entity disambiguation (via context triple) batch_69f76bc762a08190b5d29cef9923da84 completed May 3, 2026, 3:37 p.m.
Created at: April 9, 2026, 9:49 p.m.