Triple
T26060428
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Moscow Armistice with Finland |
E657241
|
entity |
| Predicate | requiredCensorshipOf |
P42543
|
FINISHED |
| Object | anti-Soviet propaganda in Finland |
—
|
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: anti-Soviet propaganda in Finland | Statement: [Moscow Armistice with Finland, requiredCensorshipOf, anti-Soviet propaganda in Finland]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: requiredCensorshipOf Context triple: [Moscow Armistice with Finland, requiredCensorshipOf, anti-Soviet propaganda in Finland]
-
A.
censorshipLevel
Indicates the degree or strictness of control, suppression, or restriction applied to information, media, or expression.
-
B.
censorshipReason
chosen
Indicates the justification or cause given for why certain content is suppressed, restricted, or removed.
-
C.
censoredSetting
Indicates that a setting or environment has been modified to restrict, remove, or obscure certain content or information.
-
D.
typeOfCensorship
Indicates the specific kind or method of censorship being applied in a given context.
-
E.
coCensorWith
Indicates that two or more entities participate together in the act of censoring the same content or subject.
- 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_69ee5bbd788481909e22bd7153d0c037 |
completed | April 26, 2026, 6:38 p.m. |
| NER | Named-entity recognition | batch_69f6d0d46aec819091edf97324d793ac |
completed | May 3, 2026, 4:36 a.m. |
| PD | Predicate disambiguation | batch_69f6cfe2183481908ae4e85a59c66f69 |
completed | May 3, 2026, 4:32 a.m. |
Created at: April 26, 2026, 7:17 p.m.