Triple
T22389166
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Good for You |
E553470
|
entity |
| Predicate | writer |
P1360
|
FINISHED |
| Object | Julia Michaels |
—
|
NE NERFINISHED |
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, writer, Julia Michaels]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Julia Michaels Context triple: [Good for You, 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 (2 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_69e11e4cf87c8190a1ff474daec326b7 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15858c13c819098fe66a50ecea7d7 |
completed | April 29, 2026, 1:01 a.m. |
Created at: April 16, 2026, 8:45 p.m.