Triple

T39046
Position Surface form Disambiguated ID Type / Status
Subject Rogers E773 entity
Predicate hasVariant P455 FINISHED
Object Rodgers E773 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: Rodgers | Statement: [Rogers, hasVariant, Rodgers]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Rodgers
Context triple: [Rogers, hasVariant, Rodgers]
  • A. Rogers chosen
    Rogers is a common English-language surname borne by numerous notable individuals across fields such as science, politics, entertainment, and sports.
  • B. Sam Jones
    Sam Jones was a Hall of Fame shooting guard who won 10 NBA championships with the Boston Celtics during the 1950s and 1960s, making him one of the most decorated players in league history.
  • C. Earle Cabell
    Earle Cabell was an American politician and businessman who served as mayor of Dallas, Texas, during the early 1960s, including at the time of President John F. Kennedy’s assassination.
  • D. Jim Loscutoff
    Jim Loscutoff was an American professional basketball forward best known for his rugged defense and seven NBA championships with the Boston Celtics in the 1950s and 1960s.
  • E. Dennis
    Dennis is a coastal town on Cape Cod in Massachusetts known for its beaches, historic charm, and popular summer tourism.
  • 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_69a247a8f6c08190bac804906d62ed5a completed Feb. 28, 2026, 1:40 a.m.
NER Named-entity recognition batch_69a24acd14b48190b80d4329621583df completed Feb. 28, 2026, 1:54 a.m.
NED1 Entity disambiguation (via context triple) batch_69a2623b6bb881909bcafff1aeb536e4 completed Feb. 28, 2026, 3:34 a.m.
Created at: Feb. 28, 2026, 1:46 a.m.