Triple

T21430230
Position Surface form Disambiguated ID Type / Status
Subject Payback E528663 entity
Predicate character P662 FINISHED
Object Bronson
Bronson is a supporting criminal character in the 1999 neo-noir crime film "Payback," involved in the gritty underworld surrounding Mel Gibson’s vengeful protagonist.
 E1483923 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: Bronson | Statement: [Payback, character, Bronson]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Bronson
Context triple: [Payback, character, Bronson]
  • A. Bronson
    Bronson is a 2008 British biographical crime film in which Tom Hardy portrays the notoriously violent prisoner Charles Bronson.
  • B. Bronson
    Bronson is a given name most notably associated with American educator and transcendentalist philosopher Amos Bronson Alcott.
  • C. Bronson
    Bronson is a small town in Levy County that serves as the county seat in North Central Florida.
  • D. Brody
    Brody is a surname of English and Irish origin borne by various notable individuals across fields such as entertainment, sports, and public life.
  • E. Brody
    Brody is a historic town in western Ukraine that has long served as a strategic military and trade crossroads in the region.
  • 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: Bronson
Triple: [Payback, character, Bronson]
Generated description
Bronson is a supporting criminal character in the 1999 neo-noir crime film "Payback," involved in the gritty underworld surrounding Mel Gibson’s vengeful protagonist.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Bronson
Target entity description: Bronson is a supporting criminal character in the 1999 neo-noir crime film "Payback," involved in the gritty underworld surrounding Mel Gibson’s vengeful protagonist.
  • A. Bronson
    Bronson is a 2008 British biographical crime film in which Tom Hardy portrays the notoriously violent prisoner Charles Bronson.
  • B. Bronson
    Bronson is a given name most notably associated with American educator and transcendentalist philosopher Amos Bronson Alcott.
  • C. Bronson
    Bronson is a small town in Levy County that serves as the county seat in North Central Florida.
  • D. Brody
    Brody is a surname of English and Irish origin borne by various notable individuals across fields such as entertainment, sports, and public life.
  • E. Brody
    Brody is a historic town in western Ukraine that has long served as a strategic military and trade crossroads in the region.
  • 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_69e0c455f3688190810bc96365791b0f completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69ee813ef6a8819089511b8f608c9491 completed April 26, 2026, 9:18 p.m.
NED1 Entity disambiguation (via context triple) batch_6a09c2ac2d188190b909826855b4d132 completed May 17, 2026, 1:29 p.m.
NEDg Description generation batch_6a09c33c37e88190b559bbf98e589487 completed May 17, 2026, 1:31 p.m.
NED2 Entity disambiguation (via description) batch_6a09c3c6a208819096b2e4a2c92b3cb0 completed May 17, 2026, 1:33 p.m.
Created at: April 16, 2026, 5:49 p.m.