Triple

T16099989
Position Surface form Disambiguated ID Type / Status
Subject Jeff Wexler E390589 entity
Predicate notableWork P4 FINISHED
Object Get Smart E137465 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: Get Smart | Statement: [Jeff Wexler, notableWork, Get Smart]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Get Smart
Context triple: [Jeff Wexler, notableWork, Get Smart]
  • A. Get Smart chosen
    Get Smart is a 2008 action-comedy film adaptation of the classic TV series, starring Steve Carell as an inept secret agent alongside Anne Hathaway.
  • B. Pretty Smart
    Pretty Smart is a Netflix comedy series following a high-strung, intellectual woman who moves in with her carefree sister and her quirky roommates, starring Emily Osment.
  • C. Smart Ass
    Smart Ass is a popular medium-roast coffee blend by Kicking Horse Coffee known for its bright, sweet, and chocolaty flavor profile.
  • D. Get Smart (TV series)
    Get Smart (TV series) is a 1960s American spy-fi comedy television show that parodies the secret agent genre through the misadventures of bumbling secret agent Maxwell Smart and his colleagues at the fictional CONTROL agency.
  • E. Smart People
    Smart People is a 2008 comedy-drama film about a widowed, self-absorbed literature professor whose life is upended by unexpected family and romantic developments.
  • 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_69d87f198bc48190a8b7e53ca15b7ead completed April 10, 2026, 4:39 a.m.
NER Named-entity recognition batch_69e1ff6756948190a7f5ecb375e59701 completed April 17, 2026, 9:37 a.m.
NED1 Entity disambiguation (via context triple) batch_69ffeb9d6140819087f9b3dc549c4aec completed May 10, 2026, 2:21 a.m.
Created at: April 10, 2026, 5 a.m.