Triple

T13481372
Position Surface form Disambiguated ID Type / Status
Subject Testament E318379 entity
Predicate mainCharacter P1183 FINISHED
Object Tom Wetherly
Tom Wetherly is the central protagonist of the post-apocalyptic drama film "Testament," around whom the story’s emotional and moral struggles unfold.
E1142967 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 Wetherly | Statement: [Testament, mainCharacter, Tom Wetherly]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tom Wetherly
Context triple: [Testament, mainCharacter, Tom Wetherly]
  • A. Ray Wright
    Ray Wright is a screenwriter known for his work on the film "Case 39" and other genre-focused screenplays.
  • B. Tom Wicker
    Tom Wicker was an influential American journalist and author best known for his political reporting and long tenure as a columnist and editor at The New York Times.
  • C. Dan Woolsey
    Dan Woolsey is an entrepreneur and media professional best known as a founder of the African American–focused news and entertainment platform TheGrio.
  • D. Dennis Awtrey
    Dennis Awtrey is a former American professional basketball center known for his defensive play and role as a key contributor on several NBA teams during the 1970s and early 1980s.
  • E. Frank Wead
    Frank Wead was an American naval aviator-turned-screenwriter known for his aviation-themed stories and contributions to classic Hollywood films.
  • 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 Wetherly
Triple: [Testament, mainCharacter, Tom Wetherly]
Generated description
Tom Wetherly is the central protagonist of the post-apocalyptic drama film "Testament," around whom the story’s emotional and moral struggles unfold.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Tom Wetherly
Target entity description: Tom Wetherly is the central protagonist of the post-apocalyptic drama film "Testament," around whom the story’s emotional and moral struggles unfold.
  • A. Ray Wright
    Ray Wright is a screenwriter known for his work on the film "Case 39" and other genre-focused screenplays.
  • B. Tom Wicker
    Tom Wicker was an influential American journalist and author best known for his political reporting and long tenure as a columnist and editor at The New York Times.
  • C. Dan Woolsey
    Dan Woolsey is an entrepreneur and media professional best known as a founder of the African American–focused news and entertainment platform TheGrio.
  • D. Dennis Awtrey
    Dennis Awtrey is a former American professional basketball center known for his defensive play and role as a key contributor on several NBA teams during the 1970s and early 1980s.
  • E. Frank Wead
    Frank Wead was an American naval aviator-turned-screenwriter known for his aviation-themed stories and contributions to classic Hollywood films.
  • 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_69d806b6bfec819089222715b2e86c8e completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69dbaf36c6b08190ba99400600e0b662 completed April 12, 2026, 2:41 p.m.
NED1 Entity disambiguation (via context triple) batch_69fed314bb9481908144c5399aa62ffa completed May 9, 2026, 6:24 a.m.
NEDg Description generation batch_69fed47c88d08190a4396b955c9bb388 completed May 9, 2026, 6:30 a.m.
NED2 Entity disambiguation (via description) batch_69fed50956408190b1426d578803974e completed May 9, 2026, 6:32 a.m.
Created at: April 9, 2026, 9:42 p.m.