Triple
T21978476
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Charles I, Duke of Brunswick-Wolfenbüttel |
E542770
|
entity |
| Predicate | governmentReformType |
P98268
|
FINISHED |
| Object | centralization of administration |
—
|
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: centralization of administration | Statement: [Charles I, Duke of Brunswick-Wolfenbüttel, governmentReformType, centralization of administration]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: governmentReformType Context triple: [Charles I, Duke of Brunswick-Wolfenbüttel, governmentReformType, centralization of administration]
-
A.
typeOfReforms
chosen
Indicates the specific kinds or categories of reforms associated with an entity or situation.
-
B.
governmentalBodyReformed
Indicates that an existing governmental body has been reorganized, restructured, or otherwise formally reformed.
-
C.
restructuredGovernmentOf
Indicates that one entity has reorganized or significantly altered the governmental structure or system of another entity.
-
D.
governmentTypeAffected
Indicates that an action, event, or condition has an impact on the form, structure, or functioning of a government type.
-
E.
reform
Indicates bringing about significant changes to an existing system, practice, or entity in order to improve or correct it.
- 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_69e0c48070988190909db97667b9a0ac |
completed | April 16, 2026, 11:14 a.m. |
| NER | Named-entity recognition | batch_69f1248a60708190a9aa8b9b7738c261 |
completed | April 28, 2026, 9:20 p.m. |
| PD | Predicate disambiguation | batch_69e6f6154e408190acc5b2c278acaff4 |
completed | April 21, 2026, 3:59 a.m. |
Created at: April 16, 2026, 8:03 p.m.