Triple

T5532778
Position Surface form Disambiguated ID Type / Status
Subject Gran Torino E145087 entity
Predicate mainCharacter P1183 FINISHED
Object Walt Kowalski
Walt Kowalski is a gruff, widowed Korean War veteran whose evolving relationship with his Hmong neighbors drives the emotional and moral core of the film "Gran Torino."
 E529157 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: Walt Kowalski | Statement: [Gran Torino, mainCharacter, Walt Kowalski]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Walt Kowalski
Context triple: [Gran Torino, mainCharacter, Walt Kowalski]
  • A. Don Galloway
    Don Galloway was an American actor best known for his role as Detective Sergeant Ed Brown on the television series "Ironside."
  • B. Lester Cole
    Lester Cole was an American screenwriter and one of the Hollywood Ten, blacklisted during the Red Scare for alleged communist affiliations.
  • C. Don Traeger
    Don Traeger is a video game industry figure best known as a co-founder of the game development studio Treyarch.
  • D. Curt Menefee
    Curt Menefee is an American sportscaster best known as the longtime studio host of Fox's NFL coverage.
  • E. Tom Langer
    Tom Langer is an individual notable enough to be recognized as a bearer of the surname Langer, though specific widely known public details about him are not clearly established.
  • 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: Walt Kowalski
Triple: [Gran Torino, mainCharacter, Walt Kowalski]
Generated description
Walt Kowalski is a gruff, widowed Korean War veteran whose evolving relationship with his Hmong neighbors drives the emotional and moral core of the film "Gran Torino."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Walt Kowalski
Target entity description: Walt Kowalski is a gruff, widowed Korean War veteran whose evolving relationship with his Hmong neighbors drives the emotional and moral core of the film "Gran Torino."
  • A. Don Galloway
    Don Galloway was an American actor best known for his role as Detective Sergeant Ed Brown on the television series "Ironside."
  • B. Lester Cole
    Lester Cole was an American screenwriter and one of the Hollywood Ten, blacklisted during the Red Scare for alleged communist affiliations.
  • C. Don Traeger
    Don Traeger is a video game industry figure best known as a co-founder of the game development studio Treyarch.
  • D. Curt Menefee
    Curt Menefee is an American sportscaster best known as the longtime studio host of Fox's NFL coverage.
  • E. Tom Langer
    Tom Langer is an individual notable enough to be recognized as a bearer of the surname Langer, though specific widely known public details about him are not clearly established.
  • 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_69c008f9955881909bfa8348b56b4739 completed March 22, 2026, 3:21 p.m.
NER Named-entity recognition batch_69c01f9ea2c88190a68642f5799bd8ff completed March 22, 2026, 4:58 p.m.
NED1 Entity disambiguation (via context triple) batch_69c028094fa48190a1f48779a7963af9 completed March 22, 2026, 5:34 p.m.
NEDg Description generation batch_69c033ddc7148190ba64ebfc2472c367 completed March 22, 2026, 6:24 p.m.
NED2 Entity disambiguation (via description) batch_69c036725fc481908ab0e260892d8243 completed March 22, 2026, 6:35 p.m.
Created at: March 22, 2026, 3:34 p.m.