Triple

T3275326
Position Surface form Disambiguated ID Type / Status
Subject All of Me E68743 entity
Predicate hasPart P35 FINISHED
Object Thank You
"Thank You" is a song featured on the jazz standard album "All of Me."
 E344635 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: Thank You | Statement: [All of Me, hasPart, Thank You]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Thank You
Context triple: [All of Me, hasPart, Thank You]
  • A. Thank You So Much
    "Thank You So Much" is a lesser-known song composed by Richard Rodgers, the influential American composer famed for his work in musical theatre.
  • B. Thank You for the Music
    "Thank You for the Music" is a popular ABBA song, later featured prominently in the musical and film "Mamma Mia!" where it is performed by the character Harry Bright among others.
  • C. I Wanna Thank Me
    "I Wanna Thank Me" is a 2019 studio album by Snoop Dogg that showcases his veteran West Coast hip-hop style and self-reflective celebration of his long career.
  • D. Praise You
    "Praise You" is a 1999 hit electronic dance track by British DJ and producer Norman Cook, better known as Fatboy Slim, renowned for its innovative sample-based production and iconic low-budget music video.
  • E. For You
    "For You" is a song by Bruce Springsteen from his debut album "Greetings from Asbury Park, N.J.," noted for its vivid storytelling and emotional intensity.
  • 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: Thank You
Triple: [All of Me, hasPart, Thank You]
Generated description
"Thank You" is a song featured on the jazz standard album "All of Me."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Thank You
Target entity description: "Thank You" is a song featured on the jazz standard album "All of Me."
  • A. Thank You So Much
    "Thank You So Much" is a lesser-known song composed by Richard Rodgers, the influential American composer famed for his work in musical theatre.
  • B. Thank You for the Music
    "Thank You for the Music" is a popular ABBA song, later featured prominently in the musical and film "Mamma Mia!" where it is performed by the character Harry Bright among others.
  • C. I Wanna Thank Me
    "I Wanna Thank Me" is a 2019 studio album by Snoop Dogg that showcases his veteran West Coast hip-hop style and self-reflective celebration of his long career.
  • D. Praise You
    "Praise You" is a 1999 hit electronic dance track by British DJ and producer Norman Cook, better known as Fatboy Slim, renowned for its innovative sample-based production and iconic low-budget music video.
  • E. For You
    "For You" is a song by Bruce Springsteen from his debut album "Greetings from Asbury Park, N.J.," noted for its vivid storytelling and emotional intensity.
  • 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_69ad859b54f881909bf530d549caf2fd completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adb0110f1c8190ae60708b686cbbf9 completed March 8, 2026, 5:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69b2e841d5588190a53ba90a46721b0f completed March 12, 2026, 4:22 p.m.
NEDg Description generation batch_69b2e8b79d308190922a310ff1337eae completed March 12, 2026, 4:24 p.m.
NED2 Entity disambiguation (via description) batch_69b2e9ba41948190b9e4f6f54f32603c completed March 12, 2026, 4:28 p.m.
Created at: March 8, 2026, 3:10 p.m.