Triple
T5459694
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kingdom of Kucha |
E122565
|
entity |
| Predicate | musicInfluenceOn |
P22766
|
FINISHED |
| Object | Tang dynasty court music |
—
|
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: Tang dynasty court music | Statement: [Kingdom of Kucha, musicInfluenceOn, Tang dynasty court music]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: musicInfluenceOn Context triple: [Kingdom of Kucha, musicInfluenceOn, Tang dynasty court music]
-
A.
hasGenreInfluenceOn
chosen
Indicates that one genre has a notable impact on shaping or influencing the characteristics, style, or development of another genre.
-
B.
effectOfSong
Indicates the influence or impact that a particular song has on something, such as a listener, mood, or situation.
-
C.
hasPopularityInfluencedBy
Indicates that the popularity level of one entity is affected or shaped by another specified factor or entity.
-
D.
influencedByGenre
Indicates that something’s characteristics, style, or development are shaped or affected by a particular genre.
-
E.
inPopularCulture
Indicates that an entity is referenced, depicted, or otherwise present within works or discussions of popular culture.
- 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_69bd46424248819085282ddf50a565f3 |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd927c946c8190aef40679199fede3 |
completed | March 20, 2026, 6:31 p.m. |
| PD | Predicate disambiguation | batch_69bd91a0d96c8190bd1299edbf764bbb |
completed | March 20, 2026, 6:27 p.m. |
Created at: March 20, 2026, 2:08 p.m.