Triple

T13912425
Position Surface form Disambiguated ID Type / Status
Subject My Favorite Things E334531 entity
Predicate track P17929 FINISHED
Object But Not for Me E119261 NE FINISHED

How this triple was built (2 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: But Not for Me | Statement: [My Favorite Things, track, But Not for Me]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: But Not for Me
Context triple: [My Favorite Things, track, But Not for Me]
  • A. But Not for Me chosen
    "But Not for Me" is a popular jazz and pop standard composed by George Gershwin with lyrics by Ira Gershwin, widely recorded by numerous artists since its 1930 debut.
  • B. If Not for You
    "If Not for You" is a 1970 folk-rock song written and first recorded by Bob Dylan, later popularized by George Harrison and Olivia Newton-John.
  • C. She’s Not for You
    "She’s Not for You" is a country song by Willie Nelson featured on his 1973 album *Shotgun Willie*.
  • D. Everything to Me
    "Everything to Me" is an R&B ballad by American singer Monica that showcases her powerful vocals and emotional storytelling about love and devotion.
  • E. Love Me Not
    "Love Me Not" is an episode of the television drama series Friday Night Lights, which follows the lives and struggles of a high school football community in small-town Texas.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69d81c5eaa9c819083b1ff8689179565 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de27245c648190b2946845ce0fdbf8 completed April 14, 2026, 11:38 a.m.
NED1 Entity disambiguation (via context triple) batch_69f7c72879e48190ac01d0a2023b098c completed May 3, 2026, 10:07 p.m.
Created at: April 9, 2026, 10:16 p.m.