Triple

T14727807
Position Surface form Disambiguated ID Type / Status
Subject Happy People/U Saved Me E345988 entity
Predicate hasPart P35 FINISHED
Object U Saved Me
"U Saved Me" is a gospel-influenced R&B song by R. Kelly that expresses gratitude for spiritual salvation and personal redemption.
 E1115285 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: U Saved Me | Statement: [Happy People/U Saved Me, hasPart, U Saved Me]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: U Saved Me
Context triple: [Happy People/U Saved Me, hasPart, U Saved Me]
  • A. Save Me
    "Save Me" is a rock song by Remy Zero best known as the theme music for the television series Smallville.
  • B. Save Me
    "Save Me" is a popular rock song by the American band Hinder, known for its post-grunge style and emotionally charged lyrics.
  • C. Save Me
    "Save Me" is a 1980 rock ballad by Queen, written by guitarist Brian May and known for its emotional lyrics and powerful vocal performance by Freddie Mercury.
  • D. Save Me
    "Save Me" is a critically acclaimed song by American singer-songwriter Aimee Mann, best known for its prominent use in the film *Magnolia* and its nomination for the Academy Award for Best Original Song.
  • E. Save Me
    "Save Me" is a 1994 American romantic comedy film starring Anne Heche and directed by Alan Roberts.
  • 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: U Saved Me
Triple: [Happy People/U Saved Me, hasPart, U Saved Me]
Generated description
"U Saved Me" is a gospel-influenced R&B song by R. Kelly that expresses gratitude for spiritual salvation and personal redemption.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: U Saved Me
Target entity description: "U Saved Me" is a gospel-influenced R&B song by R. Kelly that expresses gratitude for spiritual salvation and personal redemption.
  • A. Save Me
    "Save Me" is a popular rock song by the American band Hinder, known for its post-grunge style and emotionally charged lyrics.
  • B. Save Me
    "Save Me" is a 1980 rock ballad by Queen, written by guitarist Brian May and known for its emotional lyrics and powerful vocal performance by Freddie Mercury.
  • C. Save Me
    "Save Me" is a critically acclaimed song by American singer-songwriter Aimee Mann, best known for its prominent use in the film *Magnolia* and its nomination for the Academy Award for Best Original Song.
  • D. Save Me
    "Save Me" is a 1994 American romantic comedy film starring Anne Heche and directed by Alan Roberts.
  • E. Save Me
    "Save Me" is a song by South Korean singer Taeyeon from her album "Ytilaer," showcasing her emotive vocals and introspective pop style.
  • 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_69d822e5911c8190ba589f957dbd9ba7 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69dec26179688190ba9f3cd045da0e2a completed April 14, 2026, 10:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69fdf099eaf48190b89032b6ac769e67 completed May 8, 2026, 2:18 p.m.
NEDg Description generation batch_69fdf20f3f0c81909052226a1fb8f165 completed May 8, 2026, 2:24 p.m.
NED2 Entity disambiguation (via description) batch_69fdf30dab20819085589da4e869fb7e completed May 8, 2026, 2:28 p.m.
Created at: April 10, 2026, 1:29 a.m.