Triple
T54352
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | World Cafe Live |
E1070
|
entity |
| Predicate | genreDiversity |
P2561
|
FINISHED |
| Object | multiple music genres |
—
|
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: multiple music genres | Statement: [World Cafe Live, genreDiversity, multiple music genres]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: genreDiversity Context triple: [World Cafe Live, genreDiversity, multiple music genres]
-
A.
genre
Indicates the artistic or thematic category to which a work (such as a book, film, or song) belongs.
-
B.
musicBy
Indicates that a piece of music, performance, or recording is created, composed, or performed by a specified musical artist or group.
-
C.
musicTradition
Indicates a relationship where one entity follows, embodies, or belongs to a particular musical tradition or style associated with another entity.
-
D.
associatedMusic
Indicates a relationship where one entity is linked to or connected with a piece of music, such as being used by, related to, or thematically tied to that music.
-
E.
popularity
Indicates how widely liked, admired, or favored something or someone is by a group of people.
- 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_69a248adc5b48190aa8db9fb092fb28a |
completed | Feb. 28, 2026, 1:45 a.m. |
| NER | Named-entity recognition | batch_69a24b3a9e848190b80de3c858678b3a |
completed | Feb. 28, 2026, 1:56 a.m. |
| PD | Predicate disambiguation | batch_69a24ac52fb08190aa7c38f83434f795 |
completed | Feb. 28, 2026, 1:54 a.m. |
| PDg | Predicate description generation | batch_69a24b39eef081909cec4333f2b25513 |
completed | Feb. 28, 2026, 1:56 a.m. |
Created at: Feb. 28, 2026, 1:50 a.m.