Triple

T14660438
Position Surface form Disambiguated ID Type / Status
Subject Good for You (Selena Gomez song) E344221 entity
Predicate writer P1360 FINISHED
Object Julia Michaels E68747 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: Julia Michaels | Statement: [Good for You (Selena Gomez song), writer, Julia Michaels]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Julia Michaels
Context triple: [Good for You (Selena Gomez song), writer, Julia Michaels]
  • A. Julia Michaels chosen
    Julia Michaels is an American singer-songwriter known for her introspective pop hits and for penning songs for major artists like Justin Bieber and Selena Gomez.
  • B. Holly Goldberg Sloan
    Holly Goldberg Sloan is an American author and filmmaker best known for writing and directing family-oriented films and novels such as "Counting by 7s."
  • C. Addie Wolff
    Addie Wolff was the wife of prominent American investment banker and philanthropist Otto H. Kahn.
  • D. JP Saxe and Julia Michaels
    JP Saxe and Julia Michaels are pop singer-songwriters known for their emotive, introspective lyrics and their high-profile romantic and musical collaboration.
  • E. Rachel Antonoff
    Rachel Antonoff is an American fashion designer known for her whimsical, narrative-driven womenswear and feminist, politically engaged designs.
  • 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_69d822e283fc8190a0e4c235cf880052 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69deb51c84448190a1f5fa9ab8a1e2c4 completed April 14, 2026, 9:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69ff9976bc888190a050c2502d1f8e81 completed May 9, 2026, 8:30 p.m.
Created at: April 10, 2026, 1:27 a.m.