Triple
T12988109
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fugue in G minor, BWV 861 |
E321820
|
entity |
| Predicate | hasSubjectEntries |
P107917
|
FINISHED |
| Object | tonic and dominant |
—
|
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: tonic and dominant | Statement: [Fugue in G minor, BWV 861, hasSubjectEntries, tonic and dominant]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSubjectEntries Context triple: [Fugue in G minor, BWV 861, hasSubjectEntries, tonic and dominant]
-
A.
hasSubjectEntriesIn
Indicates that a subject is recorded or represented within specific entries of a collection, dataset, or catalog.
-
B.
hasSubjectCount
Indicates that an entity is associated with a specific number of subjects.
-
C.
hasCollectionSubject
Indicates that a collection is about or thematically centered on a particular subject.
-
D.
hasAnswerEntriesIn
Indicates that an entity has one or more answer entries stored or recorded within a specified container, context, or collection.
-
E.
hasTypicalSubject
Indicates that something is commonly or characteristically used as the subject (agent or topic) of a given relation or action.
- 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_69d8076479b8819090afce3591939cdf |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69d97f2a71a0819098bb6cf8a4b2208a |
completed | April 10, 2026, 10:52 p.m. |
| PD | Predicate disambiguation | batch_69d97dbdd94c8190ac4bbecca02dc77b |
completed | April 10, 2026, 10:46 p.m. |
| PDg | Predicate description generation | batch_69d97f1badac8190a59e60751f47b8d6 |
completed | April 10, 2026, 10:52 p.m. |
Created at: April 9, 2026, 8:41 p.m.