Triple

T4226261
Position Surface form Disambiguated ID Type / Status
Subject Clemson University E94464 entity
Predicate hasNotableAlumni P51 FINISHED
Object Brian Dawkins
Brian Dawkins is a Hall of Fame former NFL safety best known for his long, hard-hitting career with the Philadelphia Eagles.
E423615 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: Brian Dawkins | Statement: [Clemson University, hasNotableAlumni, Brian Dawkins]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Brian Dawkins
Context triple: [Clemson University, hasNotableAlumni, Brian Dawkins]
  • A. Darrell Green
    Darrell Green is a Hall of Fame NFL cornerback renowned for his exceptional speed and longevity during a 20-year career with Washington’s football franchise.
  • B. Reggie White
    Reggie White was a dominant Hall of Fame defensive end, widely regarded as one of the greatest defensive players in NFL history.
  • C. Howie Long
    Howie Long is a former NFL Hall of Fame defensive end who became a prominent football analyst and television personality.
  • D. Lawrence Taylor
    Lawrence Taylor is a legendary former NFL linebacker widely regarded as one of the greatest defensive players in football history.
  • E. Brian Westbrook
    Brian Westbrook is a former NFL running back best known for his dynamic playmaking and versatility with the Philadelphia Eagles in the 2000s.
  • 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: Brian Dawkins
Triple: [Clemson University, hasNotableAlumni, Brian Dawkins]
Generated description
Brian Dawkins is a Hall of Fame former NFL safety best known for his long, hard-hitting career with the Philadelphia Eagles.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Brian Dawkins
Target entity description: Brian Dawkins is a Hall of Fame former NFL safety best known for his long, hard-hitting career with the Philadelphia Eagles.
  • A. Darrell Green
    Darrell Green is a Hall of Fame NFL cornerback renowned for his exceptional speed and longevity during a 20-year career with Washington’s football franchise.
  • B. Reggie White
    Reggie White was a dominant Hall of Fame defensive end, widely regarded as one of the greatest defensive players in NFL history.
  • C. Howie Long
    Howie Long is a former NFL Hall of Fame defensive end who became a prominent football analyst and television personality.
  • D. Lawrence Taylor
    Lawrence Taylor is a legendary former NFL linebacker widely regarded as one of the greatest defensive players in football history.
  • E. Brian Westbrook
    Brian Westbrook is a former NFL running back best known for his dynamic playmaking and versatility with the Philadelphia Eagles in the 2000s.
  • 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_69b3453700a08190ae88792e3dc63207 completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b34e4ed34c819081d1479ce87cd78c completed March 12, 2026, 11:37 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5a85c79a881908cadc892dc30d8ef completed March 14, 2026, 6:26 p.m.
NEDg Description generation batch_69b5a9332eec8190bcc1063633f21d85 completed March 14, 2026, 6:30 p.m.
NED2 Entity disambiguation (via description) batch_69b5a99a4a9c8190a7e9bbc119d8d775 completed March 14, 2026, 6:31 p.m.
Created at: March 12, 2026, 11:04 p.m.