Triple
T2507183
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cöthen court |
E52611
|
entity |
| Predicate | employedPosition |
P2374
|
FINISHED |
| Object | Kapellmeister |
—
|
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: Kapellmeister | Statement: [Cöthen court, employedPosition, Kapellmeister]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: employedPosition Context triple: [Cöthen court, employedPosition, Kapellmeister]
-
A.
positionInWork
Indicates the specific role, rank, or placement an entity holds within a larger work or structured composition.
-
B.
employmentType
Indicates the specific kind or category of employment relationship that exists between an individual and an employer (e.g., full-time, part-time, contract).
-
C.
recipientOccupation
Indicates that the object specifies the job, profession, or role held by the recipient in the described relationship or event.
-
D.
careerStatus
Indicates the current stage, position, or condition of an entity within its professional or occupational life.
-
E.
subjectOccupation
chosen
Indicates that the subject holds or performs a particular job, profession, or role as their occupation.
- 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_69ab4958e76481908a235377dd921c9e |
completed | March 6, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69abd65d6a988190aaaac8e98540a14f |
completed | March 7, 2026, 7:40 a.m. |
| PD | Predicate disambiguation | batch_69abd0bd996c8190ba8b9d6e4333b8d4 |
completed | March 7, 2026, 7:16 a.m. |
Created at: March 6, 2026, 9:46 p.m.