Triple

T2928416
Position Surface form Disambiguated ID Type / Status
Subject Bolts E78899 entity
Predicate notableCoach P550 FINISHED
Object John Tortorella E125511 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: John Tortorella | Statement: [Bolts, notableCoach, John Tortorella]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: John Tortorella
Context triple: [Bolts, notableCoach, John Tortorella]
  • A. John Tortorella chosen
    John Tortorella is a veteran NHL coach known for his demanding, defense-first style, fiery personality, and a Stanley Cup championship with the Tampa Bay Lightning.
  • B. Phil Martelli
    Phil Martelli is an American college basketball coach best known for his long, successful tenure leading Saint Joseph's University's men's basketball program, including an undefeated regular season in 2003–04.
  • C. Ray Ferraro
    Ray Ferraro is a former Canadian professional ice hockey player and prominent NHL broadcaster known for his long playing career and work as a television analyst.
  • D. Jeff Maggioncalda
    Jeff Maggioncalda is a business executive best known for leading the online learning platform Coursera as its chief executive officer.
  • E. Joe Rinaldi
    Joe Rinaldi was an American screenwriter and story artist best known for his work on classic Walt Disney animated films in the mid-20th century.
  • 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_69ad8b0d40b481908bc2a5fa2e73c3fb completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69ad97ff0ddc8190acba9863bbe4f54b completed March 8, 2026, 3:38 p.m.
NED1 Entity disambiguation (via context triple) batch_69b1de8f4d94819086527165d7da11c5 completed March 11, 2026, 9:28 p.m.
Created at: March 8, 2026, 2:55 p.m.