Triple

T11049438
Position Surface form Disambiguated ID Type / Status
Subject Green Street E261207 entity
Predicate character P662 FINISHED
Object Matt Buckner
Matt Buckner is the American college student protagonist of the film "Green Street Hooligans," who becomes deeply involved with an English football firm after moving to London.
E904960 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: Matt Buckner | Statement: [Green Street, character, Matt Buckner]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Matt Buckner
Context triple: [Green Street, character, Matt Buckner]
  • A. John Buckner
    John Buckner is a relatively obscure individual whose primary current distinction is simply being noted as a bearer of the Buckner surname.
  • B. A. J. Buckner
    A. J. Buckner is an individual notable enough to be recognized as a namesake or prominent bearer of the surname Buckner.
  • C. Randy Buckner
    Randy Buckner is an American neuroscientist known for his influential research on the brain’s default mode network and memory using neuroimaging techniques.
  • D. Don Burnett
    Don Burnett was a British-born American actor best known for his film and television roles in the 1950s and 1960s.
  • E. Ray Heindorf
    Ray Heindorf was an American composer, arranger, and musical director best known for his work on numerous Hollywood film scores during the mid-20th century.
  • 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: Matt Buckner
Triple: [Green Street, character, Matt Buckner]
Generated description
Matt Buckner is the American college student protagonist of the film "Green Street Hooligans," who becomes deeply involved with an English football firm after moving to London.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Matt Buckner
Target entity description: Matt Buckner is the American college student protagonist of the film "Green Street Hooligans," who becomes deeply involved with an English football firm after moving to London.
  • A. John Buckner
    John Buckner is a relatively obscure individual whose primary current distinction is simply being noted as a bearer of the Buckner surname.
  • B. A. J. Buckner
    A. J. Buckner is an individual notable enough to be recognized as a namesake or prominent bearer of the surname Buckner.
  • C. Randy Buckner
    Randy Buckner is an American neuroscientist known for his influential research on the brain’s default mode network and memory using neuroimaging techniques.
  • D. Don Burnett
    Don Burnett was a British-born American actor best known for his film and television roles in the 1950s and 1960s.
  • E. Ray Heindorf
    Ray Heindorf was an American composer, arranger, and musical director best known for his work on numerous Hollywood film scores during the mid-20th century.
  • 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_69d6aa98650481908609c7c56bfa7902 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d79868c78881908c8e3672c05ae7ec completed April 9, 2026, 12:15 p.m.
NED1 Entity disambiguation (via context triple) batch_69e3e74e1dc881908afc01b328cda843 completed April 18, 2026, 8:19 p.m.
NEDg Description generation batch_69e3f01f9d048190b553184f0f6ce29c completed April 18, 2026, 8:57 p.m.
NED2 Entity disambiguation (via description) batch_69e3f3fef9308190b0354ed436c32e4c completed April 18, 2026, 9:13 p.m.
Created at: April 8, 2026, 9:26 p.m.