Triple
T13795669
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mama’s Gun |
E331506
|
entity |
| Predicate | hasTrack |
P3284
|
FINISHED |
| Object | In Love With You |
E532117
|
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: In Love With You | Statement: [Mama’s Gun, hasTrack, In Love With You]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: In Love With You Context triple: [Mama’s Gun, hasTrack, In Love With You]
-
A.
In Love With You
chosen
"In Love With You" is a soulful, jazz-inflected R&B song by Erykah Badu and Stephen Marley known for its mellow groove and romantic duet style.
-
B.
Your Love
"Your Love" is a pop and R&B song best known as a hit single co-written and produced by Pop Wansel.
-
C.
For You to Love
"For You to Love" is an R&B ballad by Freddie Jackson featured on his 1988 album "Don't Let Love Slip Away."
-
D.
Who You Love
"Who You Love" is a romantic duet by John Mayer and Katy Perry that blends soft rock and pop influences to explore the theme of accepting love without judgment.
-
E.
The One You Love
"The One You Love" is a song by Rufus Wainwright, known for its lush orchestration and introspective, emotionally charged lyrics.
- 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_69d81c58feb08190a77bca8bf7d6d20f |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de0259b0e4819081c11ced694384fb |
completed | April 14, 2026, 9:01 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7b8d893448190b37ecbf8d2ded239 |
completed | May 3, 2026, 9:06 p.m. |
Created at: April 9, 2026, 10:11 p.m.