Triple

T8872880
Position Surface form Disambiguated ID Type / Status
Subject Tom Gola E211204 entity
Predicate givenName P17 FINISHED
Object Thomas
Thomas is the given name of Tom Gola, a Hall of Fame American basketball player and coach known for his collegiate and professional success in the mid-20th century.
 E765377 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: Thomas | Statement: [Tom Gola, givenName, Thomas]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Thomas
Context triple: [Tom Gola, givenName, Thomas]
  • A. Thomas
    Thomas is the given name of Tommy Lasorda, the Hall of Fame former manager of the Los Angeles Dodgers.
  • B. Thomas
    Thomas is the given name of Thomas Osborne, 1st Duke of Leeds, a prominent 17th-century English statesman and politician.
  • C. Thomas
    Thomas is the given name of Old Tom Morris, the 19th-century Scottish golfer regarded as a pioneer and four-time Open Championship winner.
  • D. Thomas
    Thomas is the given name of Thomas Pelham-Holles, 1st Duke of Newcastle, a prominent 18th-century British Whig statesman and prime minister.
  • E. Thomas
    Thomas is the given name of Sir Thomas Frankland, a titled member of the British Frankland family.
  • 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: Thomas
Triple: [Tom Gola, givenName, Thomas]
Generated description
Thomas is the given name of Tom Gola, a Hall of Fame American basketball player and coach known for his collegiate and professional success in the mid-20th century.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Thomas
Target entity description: Thomas is the given name of Tom Gola, a Hall of Fame American basketball player and coach known for his collegiate and professional success in the mid-20th century.
  • A. Thomas
    Thomas is the full given name of Tom Thibodeau, an American professional basketball coach known for his defensive-minded teams in the NBA.
  • B. Thomas
    Thomas is the given name of Tommy Lasorda, the Hall of Fame former manager of the Los Angeles Dodgers.
  • C. Thomas
    Thomas is the full given name of Tom Brady, the legendary NFL quarterback widely regarded as one of the greatest players in American football history.
  • D. Thomas
    Thomas is the full given name of Tom Glavine, a Hall of Fame Major League Baseball pitcher best known for his career with the Atlanta Braves.
  • E. Thomas
    Thomas is the given first name of Tom Flores, the former American football quarterback and Super Bowl–winning head coach.
  • 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_69ca838e78748190934d82db3104f855 completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cc612952348190856d6964122c3f01 completed April 1, 2026, 12:04 a.m.
NED1 Entity disambiguation (via context triple) batch_69cfab68ff308190b37b2202e7ccbab3 completed April 3, 2026, 11:58 a.m.
NEDg Description generation batch_69cfaf4a62308190be31c464dbcf0429 completed April 3, 2026, 12:15 p.m.
NED2 Entity disambiguation (via description) batch_69cfaf9c335881909277236967d1ff54 completed April 3, 2026, 12:16 p.m.
Created at: March 30, 2026, 6:52 p.m.