Triple

T3871647
Position Surface form Disambiguated ID Type / Status
Subject NASCAR on Fox E92397 entity
Predicate commentaryBy P11804 FINISHED
Object Larry McReynolds
Larry McReynolds is a former NASCAR crew chief who became a prominent television racing analyst and commentator.
 E396222 NE FINISHED

How this triple was built (4 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: Larry McReynolds | Statement: [NASCAR on Fox, commentaryBy, Larry McReynolds]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Larry McReynolds
Context triple: [NASCAR on Fox, commentaryBy, Larry McReynolds]
  • A. Woody Boyd
    Woody Boyd is a naive yet lovable bartender from Indiana on the sitcom "Cheers," known for his good-natured personality and humorous, dim-witted charm.
  • B. Edwin Glenn
    Edwin Glenn was a U.S. Army officer and explorer best known for leading early 20th-century expeditions in Alaska, for whom the Glenn Highway is named.
  • C. Fred Warren
    Fred Warren was an actor known for appearing in early American cinema, including the 1929 film "Coquette."
  • D. Henry McDaniel
    Henry McDaniel was the father of Academy Award–winning actress Hattie McDaniel, known primarily in historical records for this parental connection.
  • E. Percy Wetmore
    Percy Wetmore is a cruel, sadistic prison guard in Stephen King’s novel and its film adaptation "The Green Mile," known for abusing his power over death row inmates.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Larry McReynolds
Triple: [NASCAR on Fox, commentaryBy, Larry McReynolds]
Generated description
Larry McReynolds is a former NASCAR crew chief who became a prominent television racing analyst and commentator.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Larry McReynolds
Target entity description: Larry McReynolds is a former NASCAR crew chief who became a prominent television racing analyst and commentator.
  • A. Woody Boyd
    Woody Boyd is a naive yet lovable bartender from Indiana on the sitcom "Cheers," known for his good-natured personality and humorous, dim-witted charm.
  • B. Edwin Glenn
    Edwin Glenn was a U.S. Army officer and explorer best known for leading early 20th-century expeditions in Alaska, for whom the Glenn Highway is named.
  • C. Fred Warren
    Fred Warren was an actor known for appearing in early American cinema, including the 1929 film "Coquette."
  • D. Henry McDaniel
    Henry McDaniel was the father of Academy Award–winning actress Hattie McDaniel, known primarily in historical records for this parental connection.
  • E. Percy Wetmore
    Percy Wetmore is a cruel, sadistic prison guard in Stephen King’s novel and its film adaptation "The Green Mile," known for abusing his power over death row inmates.
  • F. None of above. chosen

Provenance (5 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_69aed967448c819086c4b358d37b25aa completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aeec5691148190b469af0bee9154db completed March 9, 2026, 3:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69b51249f1ec8190a1f6cc191bc94421 completed March 14, 2026, 7:46 a.m.
NEDg Description generation batch_69b51352e2ec8190a207a6af96baaa33 completed March 14, 2026, 7:50 a.m.
NED2 Entity disambiguation (via description) batch_69b513e888008190892627805d2abd50 completed March 14, 2026, 7:53 a.m.
Created at: March 9, 2026, 3:20 p.m.