Triple

T21523664
Position Surface form Disambiguated ID Type / Status
Subject Christopher Chessun E531037 entity
Predicate predecessor P97 FINISHED
Object Tom Butler
Tom Butler is a retired Church of England bishop best known for serving as the Bishop of Southwark in London.
 E1489251 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: Tom Butler | Statement: [Christopher Chessun, predecessor, Tom Butler]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Tom Butler
Context triple: [Christopher Chessun, predecessor, Tom Butler]
  • A. Tom Butler
    Tom Butler is a Canadian actor known for his supporting roles in numerous film and television productions, including the thriller "Snakes on a Plane."
  • B. John Alfred Valentine Butler
    John Alfred Valentine Butler was a British electrochemist renowned for his foundational work on electrode kinetics, commemorated in the Butler–Volmer equation.
  • C. Peter Butler
    Peter Butler is an English football manager and former player known for coaching various national and club teams, including the Liberia national football team.
  • D. Michael Butler
    Michael Butler was an American theatrical producer best known for bringing the countercultural musical "Hair" to Broadway and later producing its 1979 film adaptation.
  • E. Michael Butler
    Michael Butler is a screenwriter best known for co-writing the 1985 Clint Eastwood Western film "Pale Rider."
  • 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: Tom Butler
Triple: [Christopher Chessun, predecessor, Tom Butler]
Generated description
Tom Butler is a retired Church of England bishop best known for serving as the Bishop of Southwark in London.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Tom Butler
Target entity description: Tom Butler is a retired Church of England bishop best known for serving as the Bishop of Southwark in London.
  • A. Tom Butler
    Tom Butler is a Canadian actor known for his supporting roles in numerous film and television productions, including the thriller "Snakes on a Plane."
  • B. John Alfred Valentine Butler
    John Alfred Valentine Butler was a British electrochemist renowned for his foundational work on electrode kinetics, commemorated in the Butler–Volmer equation.
  • C. Peter Butler
    Peter Butler is an English football manager and former player known for coaching various national and club teams, including the Liberia national football team.
  • D. Michael Butler
    Michael Butler is a screenwriter best known for co-writing the 1985 Clint Eastwood Western film "Pale Rider."
  • E. Michael Butler
    Michael Butler was an American theatrical producer best known for bringing the countercultural musical "Hair" to Broadway and later producing its 1979 film adaptation.
  • 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_69e0c45d95a081908e7962ad215da746 completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69ee884f4504819086bd632e62f02f58 completed April 26, 2026, 9:49 p.m.
NED1 Entity disambiguation (via context triple) batch_6a09e828fd6c819080e6f4a35ad68207 completed May 17, 2026, 4:09 p.m.
NEDg Description generation batch_6a09e909a4888190aa1d704eb157d86d completed May 17, 2026, 4:12 p.m.
NED2 Entity disambiguation (via description) batch_6a09ea119664819081b072c892fc0471 completed May 17, 2026, 4:17 p.m.
Created at: April 16, 2026, 6:26 p.m.