Triple
T12529145
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fugue in C major, BWV 846 |
E299513
|
entity |
| Predicate | subjectEntryType |
P22381
|
FINISHED |
| Object | stretto and sequential entries |
—
|
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: stretto and sequential entries | Statement: [Fugue in C major, BWV 846, subjectEntryType, stretto and sequential entries]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: subjectEntryType Context triple: [Fugue in C major, BWV 846, subjectEntryType, stretto and sequential entries]
-
A.
subjectType
chosen
Indicates the classification or category that defines what kind of entity the subject is.
-
B.
typicalEntryType
Indicates the usual or standard category or kind of entry associated with something.
-
C.
subjectCanBe
Indicates that the subject has the potential or capability to assume, become, or be classified as the specified object or state.
-
D.
submissionType
Indicates the specific category or format under which something is submitted (e.g., as a document, assignment, application, or other submission class).
-
E.
inscriptionContentType
Indicates the type or nature of the content conveyed by an inscription (e.g., its genre, function, or informational category).
- 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_69d6ada5cdd48190860d9ce30aff69be |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d95f5507b481908d13cc317b7402f6 |
completed | April 10, 2026, 8:36 p.m. |
| PD | Predicate disambiguation | batch_69d9540d7b788190a0d57b098e90e491 |
completed | April 10, 2026, 7:48 p.m. |
Created at: April 8, 2026, 9:57 p.m.