Triple
T23857768
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Back to the Bando |
E592356
|
entity |
| Predicate | recordingArtistCount |
P32695
|
FINISHED |
| Object | 3 |
—
|
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: 3 | Statement: [Back to the Bando, recordingArtistCount, 3]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: recordingArtistCount Context triple: [Back to the Bando, recordingArtistCount, 3]
-
A.
numberOfSingers
chosen
Indicates the quantity of singers involved in a particular performance, group, or musical context.
-
B.
artistRecorded
Indicates that an artist has recorded a particular musical work, track, or album.
-
C.
mostAwardsArtistCount
Indicates the number of artists who share the highest total count of awards within a given context.
-
D.
recordLabelArtist
Indicates that a musical artist is signed to, represented by, or releases recordings through a particular record label.
-
E.
mostFamousRecordingArtist
Indicates that the subject is the most famous recording artist associated with, or within the context of, the given entity.
- 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_69e25d22eb488190914b193aff952e83 |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f1c98bf1d081908279fc145371afa5 |
completed | April 29, 2026, 9:04 a.m. |
| PD | Predicate disambiguation | batch_69f1614612b481908c45d99e588882f9 |
completed | April 29, 2026, 1:39 a.m. |
Created at: April 17, 2026, 8:12 p.m.