Triple

T13227945
Position Surface form Disambiguated ID Type / Status
Subject smart EQ forfour E314929 entity
Predicate brand P1500 FINISHED
Object smart E80321 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: smart | Statement: [smart EQ forfour, brand, smart]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: smart
Context triple: [smart EQ forfour, brand, smart]
  • A. smart chosen
    smart is an automotive marque best known for its compact city cars and microcars, originally developed in partnership with Swatch and later owned by Mercedes-Benz.
  • B. Smart
    Smart is a surname most prominently associated in sports with Shaka Smart, a successful American college basketball coach.
  • C. SMART
    SMART is a commuter rail service operating in California’s Sonoma and Marin counties, providing passenger transportation along the North Bay corridor.
  • D. Smartism
    Smartism is a major Hindu tradition that emphasizes the worship of multiple deities as different manifestations of the one ultimate reality, often centered on Advaita Vedanta philosophy.
  • E. Get Smart
    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.
  • 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_69d806affc688190a25b6ccc588e9c72 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d98d3232d48190a3c792b025c596a6 completed April 10, 2026, 11:52 p.m.
NED1 Entity disambiguation (via context triple) batch_69f7460e94a08190a518f466f55db482 completed May 3, 2026, 12:56 p.m.
Created at: April 9, 2026, 9:21 p.m.