Triple
T21981000
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hit the Deck |
E542837
|
entity |
| Predicate | hasSong |
P20452
|
FINISHED |
| Object | Sometimes I’m 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: Sometimes I’m Happy | Statement: [Hit the Deck, hasSong, Sometimes I’m Happy]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sometimes I’m Happy Context triple: [Hit the Deck, hasSong, Sometimes I’m Happy]
-
A.
Sometimes I’m Happy
chosen
"Sometimes I’m Happy" is a popular jazz standard from the 1920s that has been widely recorded and performed by leading swing and big band artists.
-
B.
I Sing Because I’m Happy
"I Sing Because I’m Happy" is a popular contemporary gospel song, widely recognized for its uplifting lyrics and powerful choral arrangement.
-
C.
I’ll Keep You Happy
"I’ll Keep You Happy" is a song by Ike & Tina Turner, best known as the B-side to their 1966 single "River Deep – Mountain High."
-
D.
So Happy
"So Happy" is a rock song by Canadian band Theory of a Deadman, known for its dark, hard-edged sound and themes of toxic relationships.
-
E.
I’m So Happy
"I’m So Happy" is an R&B/soul song penned by American singer-songwriter and producer Prince Phillip Mitchell.
- 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_69e0c48136b081908831fa907cc02e18 |
completed | April 16, 2026, 11:14 a.m. |
| NER | Named-entity recognition | batch_69f1248cf0388190b557d065beb662b5 |
completed | April 28, 2026, 9:20 p.m. |
Created at: April 16, 2026, 8:04 p.m.