Triple
T9330021
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | "Coffee Time" sequence |
E224491
|
entity |
| Predicate | basedOnMusicGenre |
P83033
|
FINISHED |
| Object | popular song |
—
|
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: popular song | Statement: ["Coffee Time" sequence, basedOnMusicGenre, popular song]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: basedOnMusicGenre Context triple: ["Coffee Time" sequence, basedOnMusicGenre, popular song]
-
A.
styleOfMusic
Indicates the musical genre or stylistic category that characterizes a piece of music, artist, or performance.
-
B.
hasGenreInfluenceOn
Indicates that one genre has a notable impact on shaping or influencing the characteristics, style, or development of another genre.
-
C.
usedGenre
chosen
Indicates that one entity employs or is associated with a particular genre in its creation, presentation, or classification.
-
D.
influencedByGenre
Indicates that something’s characteristics, style, or development are shaped or affected by a particular genre.
-
E.
musicForGenre
Indicates that something (such as a piece, track, or work) is intended to be used as or associated with music belonging to a particular genre.
- 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_69ca8427a0c08190b749831d5ea98f02 |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd37acbc04819092a67d7f392c74cd |
completed | April 1, 2026, 3:20 p.m. |
| PD | Predicate disambiguation | batch_69cc7a643924819097f01144734901cf |
completed | April 1, 2026, 1:52 a.m. |
Created at: March 30, 2026, 7:39 p.m.