Triple
T11753279
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Grosse Fuge, Op. 133 |
E279458
|
entity |
| Predicate | subjectCount |
P101171
|
FINISHED |
| Object | multiple fugue subjects |
—
|
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: multiple fugue subjects | Statement: [Grosse Fuge, Op. 133, subjectCount, multiple fugue subjects]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: subjectCount Context triple: [Grosse Fuge, Op. 133, subjectCount, multiple fugue subjects]
-
A.
numberOfCourses
Indicates the quantity of courses associated with a given entity.
-
B.
subjectType
Indicates the classification or category that defines what kind of entity the subject is.
-
C.
numberOfProblems
Indicates the quantity or count of problems associated with a given entity or situation.
-
D.
numberOfQuestions
Indicates the total count of questions associated with or contained in a given entity or context.
-
E.
nameOfSubject
Indicates that the predicate specifies the name or label assigned to the subject entity.
- 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_69d6ab01038c819080714901502c84fc |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8a50b8a14819092a7397d73f0a8e3 |
completed | April 10, 2026, 7:21 a.m. |
| PD | Predicate disambiguation | batch_69d88a813cc48190a3dfdc60e8af80ae |
completed | April 10, 2026, 5:28 a.m. |
| PDg | Predicate description generation | batch_69d890467a2481909ce6c669e739c8de |
completed | April 10, 2026, 5:53 a.m. |
Created at: April 8, 2026, 9:41 p.m.