Triple
T22809751
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Staatsratsvorsitzender |
E564639
|
entity |
| Predicate | Aufgabenbereich |
P137086
|
FINISHED |
| Object | Unterzeichnung von Gesetzen |
—
|
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: Unterzeichnung von Gesetzen | Statement: [Staatsratsvorsitzender, Aufgabenbereich, Unterzeichnung von Gesetzen]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: Aufgabenbereich Context triple: [Staatsratsvorsitzender, Aufgabenbereich, Unterzeichnung von Gesetzen]
-
A.
competenceArea
Indicates that one entity has a particular domain, field, or area in which it possesses competence, expertise, or responsibility.
-
B.
fieldOfWork
Indicates the professional or academic domain in which an entity is primarily engaged or specializes.
-
C.
scopeOfDuty
chosen
Indicates the range or extent of responsibilities, tasks, or obligations that an entity is expected or authorized to perform.
-
D.
area of activity
Indicates the domain, field, or sphere in which an entity is active or carries out its primary functions or operations.
-
E.
oversawArea
Indicates that one entity had supervisory or managerial responsibility over a particular area, region, or domain associated with another entity.
- 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_69e245823f4c8190ade442cdcc2c224a |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f17d5f1f348190a35e87939732c99f |
completed | April 29, 2026, 3:39 a.m. |
| PD | Predicate disambiguation | batch_69eed2cb30f481909566369f515f6eff |
completed | April 27, 2026, 3:06 a.m. |
Created at: April 17, 2026, 3:32 p.m.