Triple

T1440093
Position Surface form Disambiguated ID Type / Status
Subject Inherit the Wind E31049 entity
Predicate hasCharacter P2308 FINISHED
Object Bannister
Bannister is a minor juror character in the play "Inherit the Wind," representing the everyday townspeople caught between religious fundamentalism and evolving scientific thought.
 E165253 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: Bannister | Statement: [Inherit the Wind, hasCharacter, Bannister]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Bannister
Context triple: [Inherit the Wind, hasCharacter, Bannister]
  • A. Barnett
    Barnett is a masculine given name most notably associated with the influential American abstract expressionist painter Barnett Newman.
  • B. Roger Bannister
    Roger Bannister was a British middle-distance runner and neurologist best known for being the first person to run a sub-four-minute mile.
  • C. Baines
    Baines is the middle name of Lyndon B. Johnson, the 36th president of the United States.
  • D. Frick
    Frick is a surname most prominently associated with American industrialist and art patron Henry Clay Frick.
  • E. Heinsohn
    Heinsohn is a surname most prominently associated with Tom Heinsohn, a Hall of Fame Boston Celtics player, coach, and broadcaster.
  • 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: Bannister
Triple: [Inherit the Wind, hasCharacter, Bannister]
Generated description
Bannister is a minor juror character in the play "Inherit the Wind," representing the everyday townspeople caught between religious fundamentalism and evolving scientific thought.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Bannister
Target entity description: Bannister is a minor juror character in the play "Inherit the Wind," representing the everyday townspeople caught between religious fundamentalism and evolving scientific thought.
  • A. Barnett
    Barnett is a masculine given name most notably associated with the influential American abstract expressionist painter Barnett Newman.
  • B. Roger Bannister
    Roger Bannister was a British middle-distance runner and neurologist best known for being the first person to run a sub-four-minute mile.
  • C. Baines
    Baines is the middle name of Lyndon B. Johnson, the 36th president of the United States.
  • D. Frick
    Frick is a surname most prominently associated with American industrialist and art patron Henry Clay Frick.
  • E. Heinsohn
    Heinsohn is a surname most prominently associated with Tom Heinsohn, a Hall of Fame Boston Celtics player, coach, and broadcaster.
  • 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_69a4991633388190a4d61b5a98aa407a completed March 1, 2026, 7:52 p.m.
NER Named-entity recognition batch_69a4c52e4ed881908d85e0cb9fe851ac completed March 1, 2026, 11:01 p.m.
NED1 Entity disambiguation (via context triple) batch_69ad08bc290c8190902f47f718bd4f98 completed March 8, 2026, 5:27 a.m.
NEDg Description generation batch_69ad09823ce481908b5db3ee9ebd1a88 completed March 8, 2026, 5:30 a.m.
NED2 Entity disambiguation (via description) batch_69ad0a8f17888190913c06641a6ac060 completed March 8, 2026, 5:35 a.m.
Created at: March 1, 2026, 8 p.m.