Triple

T1786043
Position Surface form Disambiguated ID Type / Status
Subject Fiona Apple E39393 entity
Predicate notableSong P4 FINISHED
Object Paper Bag
"Paper Bag" is a critically acclaimed song by American singer-songwriter Fiona Apple, known for its intricate lyrics and jazz-influenced piano-driven arrangement.
 E198282 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: Paper Bag | Statement: [Fiona Apple, notableSong, Paper Bag]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Paper Bag
Context triple: [Fiona Apple, notableSong, Paper Bag]
  • A. Papel
    Papel is an indigenous language of Guinea-Bissau spoken primarily by the Papel people in the coastal regions around Bissau.
  • B. Baggers
    Baggers is a popular nickname used by fans and media for the Carlton Football Club in the Australian Football League.
  • C. The Paper
    The Paper is a 1994 American comedy-drama film directed by Ron Howard that follows the hectic, deadline-driven day at a New York City tabloid newspaper.
  • D. Mylar
    Mylar is a durable, transparent polyester film widely used for packaging, insulation, and protective applications.
  • E. The Bag Man
    The Bag Man is a 2014 neo-noir crime thriller film starring John Cusack and Robert De Niro, centered on a hitman tasked with retrieving a mysterious bag at a remote motel.
  • 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: Paper Bag
Triple: [Fiona Apple, notableSong, Paper Bag]
Generated description
"Paper Bag" is a critically acclaimed song by American singer-songwriter Fiona Apple, known for its intricate lyrics and jazz-influenced piano-driven arrangement.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Paper Bag
Target entity description: "Paper Bag" is a critically acclaimed song by American singer-songwriter Fiona Apple, known for its intricate lyrics and jazz-influenced piano-driven arrangement.
  • A. Papel
    Papel is an indigenous language of Guinea-Bissau spoken primarily by the Papel people in the coastal regions around Bissau.
  • B. Baggers
    Baggers is a popular nickname used by fans and media for the Carlton Football Club in the Australian Football League.
  • C. The Paper
    The Paper is a 1994 American comedy-drama film directed by Ron Howard that follows the hectic, deadline-driven day at a New York City tabloid newspaper.
  • D. Mylar
    Mylar is a durable, transparent polyester film widely used for packaging, insulation, and protective applications.
  • E. The Bag Man
    The Bag Man is a 2014 neo-noir crime thriller film starring John Cusack and Robert De Niro, centered on a hitman tasked with retrieving a mysterious bag at a remote motel.
  • 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_69a88630519c8190a17addd83c4a3ef4 completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69aa650d304481908ad9bff3eadf7da6 completed March 6, 2026, 5:24 a.m.
NED1 Entity disambiguation (via context triple) batch_69ada9a476448190b072361fe4b41537 completed March 8, 2026, 4:53 p.m.
NEDg Description generation batch_69adab05cf6c81909f4713664f508ad9 completed March 8, 2026, 4:59 p.m.
NED2 Entity disambiguation (via description) batch_69adaeb20390819098bad8951ec00d00 completed March 8, 2026, 5:15 p.m.
Created at: March 4, 2026, 7:31 p.m.