Triple

T12243623
Position Surface form Disambiguated ID Type / Status
Subject Matt Kenseth E291795 entity
Predicate fullName P16 FINISHED
Object Matthew Roy Kenseth E291795 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: Matthew Roy Kenseth | Statement: [Matt Kenseth, fullName, Matthew Roy Kenseth]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Matthew Roy Kenseth
Context triple: [Matt Kenseth, fullName, Matthew Roy Kenseth]
  • A. Matt Kenseth chosen
    Matt Kenseth is an American NASCAR driver and 2003 Cup Series champion known for his consistency and success in stock car racing.
  • B. Ryan Newman
    Ryan Newman is an American professional stock car racing driver known for his long NASCAR Cup Series career, including successful stints with top teams and a reputation for strong qualifying performances.
  • C. Kevin Harvick
    Kevin Harvick is an American professional stock car racing driver and NASCAR Cup Series champion known for his long and successful career in motorsports.
  • D. Kurt Busch
    Kurt Busch is an American professional stock car racing driver and NASCAR Cup Series champion known for his long and successful career with multiple top teams.
  • E. Kyle Newman
    Kyle Newman is an American filmmaker best known for directing genre-blending comedies and action films, including the teen spy movie "Barely Lethal."
  • 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_69d6ab67950c8190be08450a06228c4b completed April 8, 2026, 7:24 p.m.
NER Named-entity recognition batch_69d91cb724448190be29fc1d2b946ab7 completed April 10, 2026, 3:52 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6555ab68881908813e45548281df3 completed May 2, 2026, 7:49 p.m.
Created at: April 8, 2026, 9:51 p.m.