Triple

T8335486
Position Surface form Disambiguated ID Type / Status
Subject Black Adam E195776 entity
Predicate editedBy P1954 FINISHED
Object Mike Sale
Mike Sale is a film editor known for his work on major Hollywood productions, including the superhero movie "Black Adam."
 E724841 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: Mike Sale | Statement: [Black Adam, editedBy, Mike Sale]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Mike Sale
Context triple: [Black Adam, editedBy, Mike Sale]
  • A. Mike Gillespie
    Mike Gillespie was a highly respected American college baseball coach best known for leading the USC Trojans to sustained success, including a national championship.
  • B. Don Saleski
    Don Saleski is a former NHL right winger best known for his gritty, physical play with the Philadelphia Flyers during their 1970s "Broad Street Bullies" era.
  • C. Mike Talman
    Mike Talman is a con man who becomes entangled in a tense scheme involving a blind woman and hidden heroin in the thriller "Wait Until Dark."
  • D. Mike Dailey
    Mike Dailey is an American arena football coach best known for leading the Albany Firebirds and later the Colorado Crush to success in the Arena Football League.
  • E. Mike McNeil
    Mike McNeil is a software developer best known as the creator of the Sails.js Node.js web framework.
  • 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: Mike Sale
Triple: [Black Adam, editedBy, Mike Sale]
Generated description
Mike Sale is a film editor known for his work on major Hollywood productions, including the superhero movie "Black Adam."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Mike Sale
Target entity description: Mike Sale is a film editor known for his work on major Hollywood productions, including the superhero movie "Black Adam."
  • A. Mike Gillespie
    Mike Gillespie was a highly respected American college baseball coach best known for leading the USC Trojans to sustained success, including a national championship.
  • B. Don Saleski
    Don Saleski is a former NHL right winger best known for his gritty, physical play with the Philadelphia Flyers during their 1970s "Broad Street Bullies" era.
  • C. Mike Talman
    Mike Talman is a con man who becomes entangled in a tense scheme involving a blind woman and hidden heroin in the thriller "Wait Until Dark."
  • D. Mike Dailey
    Mike Dailey is an American arena football coach best known for leading the Albany Firebirds and later the Colorado Crush to success in the Arena Football League.
  • E. Mike McNeil
    Mike McNeil is a software developer best known as the creator of the Sails.js Node.js web framework.
  • 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_69ca82ecbdc481908a55cad8ca062d88 completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cb7fd2ca648190991e398ba70caf8d completed March 31, 2026, 8:03 a.m.
NED1 Entity disambiguation (via context triple) batch_69cd95d9b92c8190b1eb0e64aa7ea59e completed April 1, 2026, 10:02 p.m.
NEDg Description generation batch_69cda342c10881908ebafc7853815424 completed April 1, 2026, 10:59 p.m.
NED2 Entity disambiguation (via description) batch_69cdab736f208190a90bd4344b21a22c completed April 1, 2026, 11:34 p.m.
Created at: March 30, 2026, 5:57 p.m.