Triple
T13230023
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fugue in F major, BWV 856 |
E314987
|
entity |
| Predicate | hasGenreCollection |
P40766
|
FINISHED |
| Object | keyboard fugues |
—
|
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: keyboard fugues | Statement: [Fugue in F major, BWV 856, hasGenreCollection, keyboard fugues]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasGenreCollection Context triple: [Fugue in F major, BWV 856, hasGenreCollection, keyboard fugues]
-
A.
hasGenreList
chosen
Indicates that an entity is associated with a set or list of genres that categorize or describe it.
-
B.
includedInGenreCollection
Indicates that something is a member of, or contained within, a specific genre-based collection.
-
C.
hasUseGenre
Indicates that something (such as a work, product, or item) is associated with or categorized under a particular genre for its use or purpose.
-
D.
hasGenreAsSetting
Indicates that a work’s setting is characterized by, or takes place within, a particular genre.
-
E.
hasGenreScope
Indicates that something (such as a work, collection, or classification) is limited to, defined by, or applicable within a particular genre or set of genres.
- 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_69d806affc688190a25b6ccc588e9c72 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d98d336ae08190bfc118cfbefddf84 |
completed | April 10, 2026, 11:52 p.m. |
| PD | Predicate disambiguation | batch_69d98bcb21648190aef241de1e7887e2 |
completed | April 10, 2026, 11:46 p.m. |
Created at: April 9, 2026, 9:21 p.m.