Triple
T14226171
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Do Re Mi |
E352621
|
entity |
| Predicate | notableSong |
P4
|
FINISHED |
| Object | Make Someone Happy |
E493055
|
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: Make Someone Happy | Statement: [Do Re Mi, notableSong, Make Someone Happy]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Make Someone Happy Context triple: [Do Re Mi, notableSong, Make Someone Happy]
-
A.
Make Someone Happy
chosen
"Make Someone Happy" is a jazz album by Russian-Canadian vocalist Sophie Milman, showcasing her interpretations of classic standards.
-
B.
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.
-
C.
Born to Make You Happy
"Born to Make You Happy" is a pop ballad by Britney Spears that became one of her early international hits, particularly in Europe.
-
D.
Be Happy
"Be Happy" is a song featured on the album *My Life*, likely contributing an uplifting or optimistic theme to the record.
-
E.
Make You Happy
"Make You Happy" is a song featured on Céline Dion’s 1996 album *Falling into You*.
- 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_69d8278a06e481908b5d6af0a8afe737 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de6228e53c8190abbe4e2d88a7362a |
completed | April 14, 2026, 3:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd281801488190bcb17d27ee18cde6 |
completed | May 8, 2026, 12:02 a.m. |
Created at: April 10, 2026, 1:06 a.m.