Triple
T17464857
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Now |
E425247
|
entity |
| Predicate | track |
P17929
|
FINISHED |
| Object | Let's Kiss and Make Up |
—
|
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: Let's Kiss and Make Up | Statement: [Now, track, Let's Kiss and Make Up]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Let's Kiss and Make Up Context triple: [Now, track, Let's Kiss and Make Up]
-
A.
Let's Kiss and Make Up
chosen
"Let's Kiss and Make Up" is a popular song by George and Ira Gershwin, best known for its inclusion in the musical comedy "Funny Face."
-
B.
Kiss and Make Up
"Kiss and Make Up" is a song featured on the album "Under the Blue Moon."
-
C.
Kiss Kiss
Kiss Kiss is a darkly comic short story collection by Roald Dahl, featuring macabre twists and unsettling explorations of human nature.
-
D.
Kiss Kiss
"Kiss Kiss" is a 2007 R&B/hip-hop single by Chris Brown featuring T-Pain, known for its catchy hook, dance-focused production, and commercial success on the Billboard charts.
-
E.
Just a Kiss
"Just a Kiss" is a country-pop ballad by American group Lady A that became one of their signature romantic hits in the early 2010s.
- 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_69d889dbc2e88190b18ea6115e819258 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e451a6c2e08190bca9de56ee2f5136 |
completed | April 19, 2026, 3:53 a.m. |
Created at: April 10, 2026, 5:47 a.m.