Triple

T21736212
Position Surface form Disambiguated ID Type / Status
Subject Medicine Man E536530 entity
Predicate editor P1954 FINISHED
Object John Wright
John Wright is an editor known for his work on the film "Medicine Man."
 E401239 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: John Wright | Statement: [Medicine Man, editor, John Wright]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: John Wright
Context triple: [Medicine Man, editor, John Wright]
  • A. John Wright
    John Wright is a film editor best known for his work on popular Hollywood comedies, including the Adam Sandler movie "The Waterboy."
  • B. John Wright
    John Wright was an English conspirator best known for his role in the 1605 Gunpowder Plot to assassinate King James I and blow up the Houses of Parliament.
  • C. John Wright
    John Wright was an American statesman who represented South Carolina as a delegate in the Continental Congress during the Revolutionary era.
  • D. John Wright
    John Wright is known as the husband of American actress Laura Wright, recognized for her long-running role on the soap opera "General Hospital."
  • E. John Wright
    John Wright is a theatre practitioner best known for establishing the Persephone Theatre, a prominent Canadian regional theatre company.
  • 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: John Wright
Triple: [Medicine Man, editor, John Wright]
Generated description
John Wright is an editor known for his work on the film "Medicine Man."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: John Wright
Target entity description: John Wright is an editor known for his work on the film "Medicine Man."
  • A. John Wright chosen
    John Wright is a film editor best known for his work on popular Hollywood comedies, including the Adam Sandler movie "The Waterboy."
  • B. John Wright
    John Wright was an English conspirator best known for his role in the 1605 Gunpowder Plot to assassinate King James I and blow up the Houses of Parliament.
  • C. John Wright
    John Wright was an American statesman who represented South Carolina as a delegate in the Continental Congress during the Revolutionary era.
  • D. John Wright
    John Wright is a theatre practitioner best known for establishing the Persephone Theatre, a prominent Canadian regional theatre company.
  • E. John Wright
    John Wright is known as the husband of American actress Laura Wright, recognized for her long-running role on the soap opera "General Hospital."
  • F. None of above.

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_69e0c46df5448190b4322127ffc4c690 completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69effd0c0a088190bd1926fa4b73d8f4 completed April 28, 2026, 12:19 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0a2ed417ec8190b2e5eeb991befdc6 completed May 17, 2026, 9:10 p.m.
NEDg Description generation batch_6a0a30b9aacc81909cf21733592cd462 completed May 17, 2026, 9:18 p.m.
NED2 Entity disambiguation (via description) batch_6a0a31892d108190923bdd02190bef08 completed May 17, 2026, 9:22 p.m.
Created at: April 16, 2026, 6:49 p.m.