Triple

T10836770
Position Surface form Disambiguated ID Type / Status
Subject Night School E255778 entity
Predicate starring P1507 FINISHED
Object Taran Killam E768407 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: Taran Killam | Statement: [Night School, starring, Taran Killam]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Taran Killam
Context triple: [Night School, starring, Taran Killam]
  • A. Taran Killam chosen
    Taran Killam is an American actor, comedian, and writer best known for his work as a cast member on "Saturday Night Live" and roles in various film and television comedies.
  • B. Joel McKinnon Miller
    Joel McKinnon Miller is an American character actor best known for playing the affable Detective Norm Scully on the television comedy series "Brooklyn Nine-Nine."
  • C. Rhys Darby
    Rhys Darby is a New Zealand comedian and actor known for his eccentric, high-energy roles in film and television, including prominent parts in Flight of the Conchords and various Hollywood comedies.
  • D. Marc Tarpenning
    Marc Tarpenning is an American engineer and entrepreneur best known as a co-founder of electric vehicle and clean energy company Tesla, Inc.
  • E. Kyle Howard
    Kyle Howard is an American actor best known for his comedic roles in television series and films, including prominent parts in sitcoms.
  • 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_69d6aa81a5d08190aa86689061d1ddd2 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d746ff70148190b844ab92d796af6c completed April 9, 2026, 6:28 a.m.
NED1 Entity disambiguation (via context triple) batch_69deb12aae648190aa7c93cee60ae3ea completed April 14, 2026, 9:27 p.m.
Created at: April 8, 2026, 9:19 p.m.