Triple
T11908601
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bavarian Soviet Republic |
E283334
|
entity |
| Predicate | hasCauseOfEnd |
P72156
|
FINISHED |
| Object | violent suppression |
—
|
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: violent suppression | Statement: [Bavarian Soviet Republic, hasCauseOfEnd, violent suppression]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCauseOfEnd Context triple: [Bavarian Soviet Republic, hasCauseOfEnd, violent suppression]
-
A.
hasCause
Indicates that one entity is the reason for, or brings about, the occurrence or existence of another entity or event.
-
B.
end cause
chosen
Indicates that one event or action brings about the termination or cessation of another event, state, or process.
-
C.
alsoEnded
Indicates that one event or state concluded in addition to another already mentioned event or state.
-
D.
hasConclusion
Indicates that something leads to, results in, or is associated with a particular conclusion.
-
E.
hasEnd
Indicates that one entity serves as the terminal point, boundary, or conclusion of another entity or process.
- 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_69d6ab2c07e88190ba13b0d21fd6cf33 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d8e5264b2081909bda6c24abb89725 |
completed | April 10, 2026, 11:55 a.m. |
| PD | Predicate disambiguation | batch_69d8bb3632ac8190b13e53c2b5db7125 |
completed | April 10, 2026, 8:56 a.m. |
Created at: April 8, 2026, 9:44 p.m.