Triple
T15349462
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Losing My Religion |
E367011
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object | Wanna Be Happy? |
E367016
|
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: Wanna Be Happy? | Statement: [Losing My Religion, hasPart, Wanna Be Happy?]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wanna Be Happy? Context triple: [Losing My Religion, hasPart, Wanna Be Happy?]
-
A.
Wanna Be Happy?
chosen
"Wanna Be Happy?" is a contemporary gospel song by Kirk Franklin that blends inspirational lyrics with R&B-influenced production and became one of his notable modern hits.
-
B.
I Want to Be Happy
"I Want to Be Happy" is a jazz standard from the 1925 musical "No, No, Nanette," widely performed and recorded by numerous jazz artists.
-
C.
Be Happy
"Be Happy" is a song featured on the album *My Life*, likely contributing an uplifting or optimistic theme to the record.
-
D.
Wanna Be
"Wanna Be" is a track by the electronic music collective Hive Mind, reflecting their experimental, atmospheric sound.
-
E.
Are You Happy Now?
"Are You Happy Now?" is a 2003 pop-rock single by American singer-songwriter Michelle Branch, known for its emotionally charged lyrics about heartbreak and empowerment.
- 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_69d85a1355608190a6673ddb67231d54 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e03e27f8a88190a0f65756e3a1fdfc |
completed | April 16, 2026, 1:40 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff01fb46b48190a030e40ee0163559 |
completed | May 9, 2026, 9:44 a.m. |
Created at: April 10, 2026, 3:17 a.m.