Triple
T18187677
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | If I Fell |
E435455
|
entity |
| Predicate | bSideOf |
P15273
|
FINISHED |
| Object | And I Love Her |
—
|
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: And I Love Her | Statement: [If I Fell, bSideOf, And I Love Her]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: And I Love Her Context triple: [If I Fell, bSideOf, And I Love Her]
-
A.
And I Love Her
chosen
"And I Love Her" is a romantic ballad by the Beatles, written primarily by Paul McCartney, noted for its gentle melody and acoustic arrangement.
-
B.
I Love Her
"I Love Her" is a song by Ray Ray, known for its smooth R&B style and romantic lyrics.
-
C.
Do You Love Her
"Do You Love Her" is a song featured on the album "Romance Dance" by Kim Carnes.
-
D.
Ma, I Don't Love Her
"Ma, I Don't Love Her" is a hip-hop track by the duo Clipse, known for its storytelling about complicated relationships over a Neptunes-produced beat.
-
E.
I Think I Love Her
"I Think I Love Her" is a track by Lil Wayne featured on his 2009 mixtape "No Ceilings," known for its inventive wordplay and freestyle-style delivery over a borrowed beat.
- 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_69d8b90c7ec081909b4694ccecb449c6 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4dfff86b8819080324aafba77acf3 |
completed | April 19, 2026, 2 p.m. |
Created at: April 10, 2026, 10:31 a.m.