Triple

T6067095
Position Surface form Disambiguated ID Type / Status
Subject Solar Opposites E135186 entity
Predicate developer P73 FINISHED
Object Mike McMahan E578538 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: Mike McMahan | Statement: [Solar Opposites, developer, Mike McMahan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mike McMahan
Context triple: [Solar Opposites, developer, Mike McMahan]
  • A. Mike McMahan chosen
    Mike McMahan is an American television writer and producer best known for his work on animated series such as Solar Opposites and Star Trek: Lower Decks.
  • B. Michael McMahan
    Michael McMahan is an American musician best known as a guitarist associated with the influential post-rock band Slint.
  • C. Mike McNeil
    Mike McNeil is a software developer best known as the creator of the Sails.js Node.js web framework.
  • D. Cal McVey
    Cal McVey was a 19th-century American baseball player and one of the sport’s earliest professional stars, known for his versatility in the infield and outfield.
  • E. Michael McCusker
    Michael McCusker is an American film editor known for his work on major Hollywood productions, including the thriller "The Girl on the Train" (2016).
  • 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_69c00879e8048190b690717d19c5bc03 completed March 22, 2026, 3:19 p.m.
NER Named-entity recognition batch_69c0573f17088190a728f1c290cc9d1d completed March 22, 2026, 8:55 p.m.
NED1 Entity disambiguation (via context triple) batch_69c243af0a108190a315314376332ec6 completed March 24, 2026, 7:56 a.m.
Created at: March 22, 2026, 4:10 p.m.