Triple
T23373583
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Charles Kelley |
E593544
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Just a Kiss |
—
|
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: Just a Kiss | Statement: [Charles Kelley, notableWork, Just a Kiss]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Just a Kiss Context triple: [Charles Kelley, notableWork, Just a Kiss]
-
A.
Just a Kiss
chosen
"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.
-
B.
Just a Kiss
Just a Kiss is a 2002 dark romantic comedy film known for its stylized, surreal storytelling and ensemble cast.
-
C.
A Kiss
"A Kiss" is a song by the hip hop duo Bad Meets Evil, featured on their 2011 EP *Hell: The Sequel*.
-
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.
Kiss Kiss
Kiss Kiss is a darkly comic short story collection by Roald Dahl, featuring macabre twists and unsettling explorations of human nature.
- 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_69e25d268a50819095f2fd479da8ef3f |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f1a3b0bc3c8190b1093f7ea29d015c |
completed | April 29, 2026, 6:22 a.m. |
Created at: April 17, 2026, 5:33 p.m.