Triple
T2357042
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eastern Bloc |
E47579
|
entity |
| Predicate | hadCensorship |
P17134
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Eastern Bloc, hadCensorship, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hadCensorship Context triple: [Eastern Bloc, hadCensorship, yes]
-
A.
hasCensorshipHistory
chosen
Indicates that an entity has previously been subject to censorship or involved in acts of censoring content.
-
B.
censorshipYear
Indicates the year in which an act of censorship was imposed on the referenced content or entity.
-
C.
canCensure
Indicates that one entity has the authority or power to formally reprimand, criticize, or express disapproval of another entity’s actions or behavior.
-
D.
revisedVersionCensorshipStatus
Indicates the censorship or restriction status applied to a revised version of some original content.
-
E.
wasOnceOutlawed
Indicates that an entity was previously considered illegal or banned by an authority but is no longer outlawed.
- 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_69a88a1b678c8190bce986922ba60ce0 |
completed | March 4, 2026, 7:38 p.m. |
| NER | Named-entity recognition | batch_69abcb802da08190980100444010f91e |
completed | March 7, 2026, 6:53 a.m. |
| PD | Predicate disambiguation | batch_69abc5981ce48190a3f7852d28276e11 |
completed | March 7, 2026, 6:28 a.m. |
Created at: March 4, 2026, 7:54 p.m.