Triple
T26767743
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Black & White Records |
E674988
|
entity |
| Predicate | recordedGenreArtist |
P170633
|
FINISHED |
| Object | jazz musicians |
—
|
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: jazz musicians | Statement: [Black & White Records, recordedGenreArtist, jazz musicians]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: recordedGenreArtist Context triple: [Black & White Records, recordedGenreArtist, jazz musicians]
-
A.
recordedWithArtist
Indicates that one artist participated in a recording together with another artist.
-
B.
hasGenreArtist
Indicates that an artist is associated with or specializes in a particular genre.
-
C.
artistRecorded
Indicates that an artist has recorded a particular musical work, track, or album.
-
D.
hasArtistGenre
Indicates that an artist is associated with or categorized under a particular musical or artistic genre.
-
E.
genreOfRecordedWork
Indicates that a recorded work (such as a song, album, or audio piece) belongs to a particular artistic or musical genre.
- 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_69eecda85298819097ee1c38a3d772e7 |
completed | April 27, 2026, 2:44 a.m. |
| NER | Named-entity recognition | batch_69f693ffa7908190aa4c451b16df9be6 |
completed | May 3, 2026, 12:17 a.m. |
| PD | Predicate disambiguation | batch_69f690eb1e948190aab41a89969519a5 |
completed | May 3, 2026, 12:03 a.m. |
| PDg | Predicate description generation | batch_69f6938244648190a553b532387b812c |
completed | May 3, 2026, 12:14 a.m. |
Created at: April 27, 2026, 4 a.m.