Triple

T12905852
Position Surface form Disambiguated ID Type / Status
Subject The Nylon Curtain E308726 entity
Predicate sideOneTrack P25310 FINISHED
Object Laura
"Laura" is a song by Billy Joel from his 1982 album *The Nylon Curtain*, known for its dark, emotionally complex lyrics and Beatles-influenced production.
E1016560 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: Laura | Statement: [The Nylon Curtain, sideOneTrack, Laura]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Laura
Context triple: [The Nylon Curtain, sideOneTrack, Laura]
  • A. Laura
    Laura is a feminine given name of Latin origin, commonly used in many languages and cultures.
  • B. Laura
    Laura is a classic 1944 American film noir mystery celebrated for its sophisticated storytelling, atmospheric cinematography, and iconic score.
  • C. Laura Jeanne
    Laura Jeanne is the birth name of American actress and producer Reese Witherspoon, known for films like "Legally Blonde" and "Walk the Line."
  • D. Lisa
    Lisa is the given name of Australian musician and composer Lisa Gerrard, renowned for her work as part of Dead Can Dance and for her film scores.
  • E. Lisa
    Lisa is the central protagonist of the film "Wicker Park," around whom the story’s romantic mystery and emotional tension revolve.
  • 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: Laura
Triple: [The Nylon Curtain, sideOneTrack, Laura]
Generated description
"Laura" is a song by Billy Joel from his 1982 album *The Nylon Curtain*, known for its dark, emotionally complex lyrics and Beatles-influenced production.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Laura
Target entity description: "Laura" is a song by Billy Joel from his 1982 album *The Nylon Curtain*, known for its dark, emotionally complex lyrics and Beatles-influenced production.
  • A. Laura
    Laura is a feminine given name of Latin origin, commonly used in many languages and cultures.
  • B. Laura
    Laura is a classic 1944 American film noir mystery celebrated for its sophisticated storytelling, atmospheric cinematography, and iconic score.
  • C. Laura Jeanne
    Laura Jeanne is the birth name of American actress and producer Reese Witherspoon, known for films like "Legally Blonde" and "Walk the Line."
  • D. Lisa
    Lisa is the given name of Australian musician and composer Lisa Gerrard, renowned for her work as part of Dead Can Dance and for her film scores.
  • E. Lisa
    Lisa is the central protagonist of the film "Wicker Park," around whom the story’s romantic mystery and emotional tension revolve.
  • 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_69d7bdf92b588190acdf2a2291ac4590 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d971831bd48190b0ecd13e7181bbc6 completed April 10, 2026, 9:54 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6c0e7e9fc8190ad065a587c6c45dd completed May 3, 2026, 3:28 a.m.
NEDg Description generation batch_69f6c5b5126081909e1f587b571a7f4e completed May 3, 2026, 3:49 a.m.
NED2 Entity disambiguation (via description) batch_69f6c635fc888190891a79da9d7984a0 completed May 3, 2026, 3:51 a.m.
Created at: April 9, 2026, 5:41 p.m.