Triple
T30040132
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Slippin’ Around |
E763274
|
entity |
| Predicate | hasBsideForWhitingWakelySingle |
P15273
|
FINISHED |
| Object | Wedding Bells |
—
|
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: Wedding Bells | Statement: [Slippin’ Around, hasBsideForWhitingWakelySingle, Wedding Bells]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBsideForWhitingWakelySingle Context triple: [Slippin’ Around, hasBsideForWhitingWakelySingle, Wedding Bells]
-
A.
hasBside
chosen
Indicates that one item serves as the B-side counterpart or secondary track associated with another primary item, typically in a recording or media release.
-
B.
singleSideOf
Indicates that one entity constitutes a single side or face of another entity, typically within a larger multi-sided structure or object.
-
C.
singleAorBside
Indicates that exactly one of the two related entities is on side A or side B, but not both simultaneously.
-
D.
hasASideOf
Indicates that one entity possesses or includes a particular side or face as part of its structure or boundary.
-
E.
singleSide
Indicates that the relationship or action involves only one side or participant, without a corresponding or reciprocal counterpart.
- F. None of above.
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_69f2246fb2b88190acff36bf7975c8f0 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f679d77bf8819087c1350088890b9f |
completed | May 2, 2026, 10:25 p.m. |
| PD | Predicate disambiguation | batch_69f673c664f08190b4d66cdc305e10db |
completed | May 2, 2026, 9:59 p.m. |
Created at: April 29, 2026, 6:52 p.m.