Triple
T20334861
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SWV |
E492582
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | I'm So Into You |
—
|
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: I'm So Into You | Statement: [SWV, notableWork, I'm So Into You]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: I'm So Into You Context triple: [SWV, notableWork, I'm So Into You]
-
A.
I'm So Into You
chosen
"I'm So Into You" is an R&B/soul song by American singer Peabo Bryson, known for its smooth vocals and romantic style.
-
B.
I’m Into You
"I'm Into You" is a pop-R&B song by Jennifer Lopez featuring Lil Wayne from her 2011 album "Love?" that achieved international chart success.
-
C.
So Into You
"So Into You" is a soft rock hit song by the Atlanta Rhythm Section, released in 1977 and known for its smooth melody and romantic lyrics.
-
D.
I Love You So
"I Love You So" is a popular song written by American lyricist and vaudevillian Bert Kalmar.
-
E.
Getting Into You
"Getting Into You" is a Christian pop-punk/rock song by Relient K known for its heartfelt lyrics about devotion and faith.
- 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_69e0b4a1a09881908d97270d6971a25a |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e677ea8a088190b2b37accd6b24277 |
completed | April 20, 2026, 7 p.m. |
Created at: April 16, 2026, 11:23 a.m.