Triple

T9403612
Position Surface form Disambiguated ID Type / Status
Subject Ken Eikenberry E226535 entity
Predicate givenName P17 FINISHED
Object Ken
Ken is a masculine given name commonly used in English-speaking countries, often as a short form of Kenneth.
 E795904 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 Eikenberry, givenName, Ken]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Ken
Context triple: [Ken Eikenberry, givenName, Ken]
  • A. 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.
  • B. Ken
    Ken is the iconic male doll character and Barbie’s counterpart, portrayed in the 2023 film as a comically self-aware and insecure figure exploring identity and patriarchy.
  • C. Ken
    Ken is a character in Leslie Marmon Silko’s short story "The Man to Send Rain Clouds," which explores Native American traditions and cultural conflict.
  • D. Kevin
    Kevin is a common masculine given name of Irish origin, meaning "handsome" or "kind."
  • E. 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.
  • 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 Eikenberry, givenName, Ken]
Generated description
Ken is a masculine given name commonly used in English-speaking countries, often as a short form of Kenneth.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Ken
Target entity description: Ken is a masculine given name commonly used in English-speaking countries, often as a short form of Kenneth.
  • A. 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.
  • B. Ken
    Ken is the iconic male doll character and Barbie’s counterpart, portrayed in the 2023 film as a comically self-aware and insecure figure exploring identity and patriarchy.
  • C. Ken
    Ken is a character in Leslie Marmon Silko’s short story "The Man to Send Rain Clouds," which explores Native American traditions and cultural conflict.
  • D. Kevin
    Kevin is a common masculine given name of Irish origin, meaning "handsome" or "kind."
  • E. 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.
  • 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_69ca843170f88190800a8ab2b5fc568e completed March 30, 2026, 2:09 p.m.
NER Named-entity recognition batch_69cd51bf7e5c8190850b671778496150 completed April 1, 2026, 5:11 p.m.
NED1 Entity disambiguation (via context triple) batch_69d1013279d88190aac1d25cc6aeb1fb completed April 4, 2026, 12:16 p.m.
NEDg Description generation batch_69d101bf84548190a28e5f24aff265b1 completed April 4, 2026, 12:19 p.m.
NED2 Entity disambiguation (via description) batch_69d1025ebf5c8190914b682117b01827 completed April 4, 2026, 12:21 p.m.
Created at: March 30, 2026, 7:46 p.m.