Triple
T20410537
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Whatever Gets You Through the Day |
E500575
|
entity |
| Predicate | hasSingle |
P3282
|
FINISHED |
| Object | Happy |
—
|
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: Happy | Statement: [Whatever Gets You Through the Day, hasSingle, Happy]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Happy Context triple: [Whatever Gets You Through the Day, hasSingle, Happy]
-
A.
Happy
Happy is the nickname of Happy Felsch, an early 20th-century American Major League Baseball outfielder best known for his role in the 1919 Chicago White Sox "Black Sox" scandal.
-
B.
Happy
chosen
"Happy" is a song featured as a part of the Justin Bieber concert film and soundtrack "Never Say Never."
-
C.
Happy
"Happy" is a globally popular, upbeat pop-soul song by Pharrell Williams known for its infectious melody and feel-good message.
-
D.
Happy
Happy is the younger son of Willy Loman in Arthur Miller's play "Death of a Salesman," known for his womanizing, insecurity, and pursuit of superficial success.
-
E.
Happy
Happy is one of the Seven Dwarfs from Disney's "Snow White and the Seven Dwarfs," characterized by his cheerful and optimistic personality.
- 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_69e0b4a935588190b9446a99b37ced44 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e67a3ecb348190ae777f6276037828 |
completed | April 20, 2026, 7:10 p.m. |
Created at: April 16, 2026, 11:29 a.m.