Triple

T16330178
Position Surface form Disambiguated ID Type / Status
Subject George Antheil E396529 entity
Predicate wrote P2831 FINISHED
Object Bad Boy of Music
Bad Boy of Music is the autobiographical book by American avant-garde composer George Antheil, recounting his provocative life and radical musical career in the early 20th century.
 E1206578 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: Bad Boy of Music | Statement: [George Antheil, wrote, Bad Boy of Music]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Bad Boy of Music
Context triple: [George Antheil, wrote, Bad Boy of Music]
  • A. Bad Boy
    Bad Boy is a 1949 American crime drama film about a troubled juvenile delinquent given a final chance at reform.
  • B. American Bad Boy
    American Bad Boy is an independent urban drama film featuring Torrei Hart in a prominent role.
  • C. Mr. Bad Guy
    Mr. Bad Guy is Freddie Mercury’s 1985 debut solo studio album, showcasing his distinctive vocals in a blend of pop, rock, and disco influences.
  • D. Trouble Maker
    Trouble Maker is a punk rock song by the American band Rancid, known for its fast tempo, gritty vocals, and politically charged lyrics.
  • E. Born to Be Bad
    Born to Be Bad is a 1950 film noir–style drama starring Joan Fontaine as a manipulative social climber entangled in romance and deceit.
  • 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: Bad Boy of Music
Triple: [George Antheil, wrote, Bad Boy of Music]
Generated description
Bad Boy of Music is the autobiographical book by American avant-garde composer George Antheil, recounting his provocative life and radical musical career in the early 20th century.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Bad Boy of Music
Target entity description: Bad Boy of Music is the autobiographical book by American avant-garde composer George Antheil, recounting his provocative life and radical musical career in the early 20th century.
  • A. Bad Boy
    Bad Boy is a 1949 American crime drama film about a troubled juvenile delinquent given a final chance at reform.
  • B. American Bad Boy
    American Bad Boy is an independent urban drama film featuring Torrei Hart in a prominent role.
  • C. Mr. Bad Guy
    Mr. Bad Guy is Freddie Mercury’s 1985 debut solo studio album, showcasing his distinctive vocals in a blend of pop, rock, and disco influences.
  • D. Trouble Maker
    Trouble Maker is a punk rock song by the American band Rancid, known for its fast tempo, gritty vocals, and politically charged lyrics.
  • E. Born to Be Bad
    Born to Be Bad is a 1950 film noir–style drama starring Joan Fontaine as a manipulative social climber entangled in romance and deceit.
  • 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_69d87f255b788190a400eba031dd85d8 completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e2c4debef08190a64f13214bfa098f completed April 17, 2026, 11:40 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00261134108190812da262b424a476 completed May 10, 2026, 6:30 a.m.
NEDg Description generation batch_6a0026c9b5c481908f60d2ebfb3f71d7 completed May 10, 2026, 6:33 a.m.
NED2 Entity disambiguation (via description) batch_6a00273dd8fc8190b84b8a96442781ee completed May 10, 2026, 6:35 a.m.
Created at: April 10, 2026, 5:07 a.m.