Triple
T23250079
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Billboard Music Award for Top Selling Song |
E581708
|
entity |
| Predicate | formatScope |
P151537
|
FINISHED |
| Object | all single formats |
—
|
LITERAL FINISHED |
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: all single formats | Statement: [Billboard Music Award for Top Selling Song, formatScope, all single formats]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: formatScope Context triple: [Billboard Music Award for Top Selling Song, formatScope, all single formats]
-
A.
formatContext
Indicates the contextual or situational conditions under which a particular format is defined, applied, or interpreted.
-
B.
encodingScope
Indicates the range or extent of content or information that is covered, represented, or captured by a particular encoding.
-
C.
definesScopeFor
Indicates that one entity establishes or delimits the scope, boundaries, or applicability within which another entity operates or is interpreted.
-
D.
formatLevel
Indicates the degree or style in which something is formatted or structured.
-
E.
formatPartOf
Indicates that one entity functions as a component or segment within the overall structure or composition of another entity.
- F. None of above. chosen
Provenance (4 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_69e24606b17c81908aba1a4911c8a8ba |
completed | April 17, 2026, 2:39 p.m. |
| NER | Named-entity recognition | batch_69f193f5aa9081909775fb7f7dc660b3 |
completed | April 29, 2026, 5:15 a.m. |
| PD | Predicate disambiguation | batch_69effce4d704819092826931d430e8c4 |
completed | April 28, 2026, 12:18 a.m. |
| PDg | Predicate description generation | batch_69f01d8770d081908897c28b04e5faea |
completed | April 28, 2026, 2:37 a.m. |
Created at: April 17, 2026, 4:10 p.m.