Triple

T1072680
Position Surface form Disambiguated ID Type / Status
Subject Ken Dryden E23363 entity
Predicate nickname P55 FINISHED
Object Ken
Ken is the nickname of Ken Dryden, the legendary Canadian Hall of Fame goaltender best known for backstopping the Montreal Canadiens to multiple Stanley Cup championships in the 1970s.
 E123246 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: Ken | Statement: [Ken Dryden, nickname, Ken]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Ken
Context triple: [Ken Dryden, nickname, Ken]
  • A. Kevin
    Kevin is the given name of Kevin Garnett, a Hall of Fame American professional basketball player known for his intensity, versatility, and NBA championship with the Boston Celtics.
  • B. Kenny
    "Kenny" is a 1979 country music album by American singer Kenny Rogers that features several of his popular hits from that era.
  • C. Kenneth
    Kenneth is the formal given name of American country music singer, songwriter, and actor Kenny Rogers.
  • D. Kim
    Kim is the given name of American singer-songwriter Kim Carnes, best known for her hit song "Bette Davis Eyes."
  • E. Don
    The Don is a major river in southwestern Russia that flows from the Central Russian Upland to the Sea of Azov, historically serving as an important trade route and cultural boundary.
  • 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: Ken
Triple: [Ken Dryden, nickname, Ken]
Generated description
Ken is the nickname of Ken Dryden, the legendary Canadian Hall of Fame goaltender best known for backstopping the Montreal Canadiens to multiple Stanley Cup championships in the 1970s.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Ken
Target entity description: Ken is the nickname of Ken Dryden, the legendary Canadian Hall of Fame goaltender best known for backstopping the Montreal Canadiens to multiple Stanley Cup championships in the 1970s.
  • A. Kevin
    Kevin is the given name of Kevin Garnett, a Hall of Fame American professional basketball player known for his intensity, versatility, and NBA championship with the Boston Celtics.
  • B. Kenny
    "Kenny" is a 1979 country music album by American singer Kenny Rogers that features several of his popular hits from that era.
  • C. Kenneth
    Kenneth is the formal given name of American country music singer, songwriter, and actor Kenny Rogers.
  • D. Kim
    Kim is the given name of American singer-songwriter Kim Carnes, best known for her hit song "Bette Davis Eyes."
  • E. Don
    The Don is a major river in southwestern Russia that flows from the Central Russian Upland to the Sea of Azov, historically serving as an important trade route and cultural boundary.
  • 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_69a493ee1f908190992b5f0d1b04459b completed March 1, 2026, 7:30 p.m.
NER Named-entity recognition batch_69a4b92afad88190b7705923f71fc760 completed March 1, 2026, 10:09 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac42a9af14819091d4f2578c6b1c02 completed March 7, 2026, 3:22 p.m.
NEDg Description generation batch_69ac434b7ea081909d5608831e29b5a9 completed March 7, 2026, 3:24 p.m.
NED2 Entity disambiguation (via description) batch_69ac43b393748190a5fa81b7ab7fa911 completed March 7, 2026, 3:26 p.m.
Created at: March 1, 2026, 7:42 p.m.