Triple
T9905687
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Keep That Same Energy |
E185004
|
entity |
| Predicate | hasTrack |
P3284
|
FINISHED |
| Object | Gonna Love Me |
E188267
|
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: Gonna Love Me | Statement: [Keep That Same Energy, hasTrack, Gonna Love Me]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gonna Love Me Context triple: [Keep That Same Energy, hasTrack, Gonna Love Me]
-
A.
Gonna Love Me
chosen
"Gonna Love Me" is a soulful R&B song by Teyana Taylor that blends nostalgic 1990s influences with contemporary production and intimate, confessional lyrics.
-
B.
Are You Gonna Love Me
"Are You Gonna Love Me" is a song featured on the R&B album "Any Love" by Luther Vandross.
-
C.
Please Love Me
"Please Love Me" is a blues song popularized by B.B. King, showcasing his expressive guitar work and emotive vocal style.
-
D.
The Love in Me
"The Love in Me" is a song featured on the Christian music album "Something About Faith."
-
E.
Do You Love Me
"Do You Love Me" is a 1962 Motown hit song, originally recorded by The Contours, that became famous for its energetic vocals and dance-oriented rhythm.
- 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_69ca8296165881908ca4750701af1f29 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cdb50cf8808190a41e565216712704 |
completed | April 2, 2026, 12:15 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1eb316a188190a1c7fbe0d1997cf5 |
completed | April 5, 2026, 4:55 a.m. |
Created at: March 30, 2026, 8:40 p.m.