Triple

T3819812
Position Surface form Disambiguated ID Type / Status
Subject More American Graffiti E84344 entity
Predicate featuresCharacter P626 FINISHED
Object Bob Falfa
Bob Falfa is a hot-rod-driving character originally from the film "American Graffiti," known for his cocky attitude and street-racing bravado.
 E390603 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: Bob Falfa | Statement: [More American Graffiti, featuresCharacter, Bob Falfa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Bob Falfa
Context triple: [More American Graffiti, featuresCharacter, Bob Falfa]
  • A. Laramie Eppler
    Laramie Eppler is an American actor best known for his role as one of the young brothers in Terrence Malick’s acclaimed film "The Tree of Life."
  • B. Michael O’Keefe
    Michael O’Keefe is an American actor best known for his role as young caddie Danny Noonan in the classic comedy film "Caddyshack."
  • C. Don Traeger
    Don Traeger is a video game industry figure best known as a co-founder of the game development studio Treyarch.
  • D. Wilbur Fisk
    Wilbur Fisk was a prominent 19th-century American Methodist minister and educator who served as the first president of Wesleyan University in Middletown, Connecticut.
  • E. Bob Roberts
    Bob Roberts was a film producer active in mid-20th-century American cinema, notably involved in classic Hollywood productions.
  • 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: Bob Falfa
Triple: [More American Graffiti, featuresCharacter, Bob Falfa]
Generated description
Bob Falfa is a hot-rod-driving character originally from the film "American Graffiti," known for his cocky attitude and street-racing bravado.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Bob Falfa
Target entity description: Bob Falfa is a hot-rod-driving character originally from the film "American Graffiti," known for his cocky attitude and street-racing bravado.
  • A. Laramie Eppler
    Laramie Eppler is an American actor best known for his role as one of the young brothers in Terrence Malick’s acclaimed film "The Tree of Life."
  • B. Michael O’Keefe
    Michael O’Keefe is an American actor best known for his role as young caddie Danny Noonan in the classic comedy film "Caddyshack."
  • C. Don Traeger
    Don Traeger is a video game industry figure best known as a co-founder of the game development studio Treyarch.
  • D. Wilbur Fisk
    Wilbur Fisk was a prominent 19th-century American Methodist minister and educator who served as the first president of Wesleyan University in Middletown, Connecticut.
  • E. Bob Roberts
    Bob Roberts was a film producer active in mid-20th-century American cinema, notably involved in classic Hollywood productions.
  • 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_69aed931f5908190be2c07af66d4df25 completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aeea601d408190b09dc486e77488d4 completed March 9, 2026, 3:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69b4fb466a108190ac203ee00ce58f04 completed March 14, 2026, 6:08 a.m.
NEDg Description generation batch_69b4fc08d65081908953482b10fa5611 completed March 14, 2026, 6:11 a.m.
NED2 Entity disambiguation (via description) batch_69b4fc7d8cf081909c4447818b5363c5 completed March 14, 2026, 6:13 a.m.
Created at: March 9, 2026, 3:17 p.m.