Triple
T2279507
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Emile, or On Education |
E51248
|
entity |
| Predicate | reasonForCensorship |
P33526
|
FINISHED |
| Object | religious heterodoxy |
—
|
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: religious heterodoxy | Statement: [Emile, or On Education, reasonForCensorship, religious heterodoxy]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: reasonForCensorship Context triple: [Emile, or On Education, reasonForCensorship, religious heterodoxy]
-
A.
repressedDissent
Indicates that one party has actively suppressed or stifled opposition, criticism, or disagreement from another party or group.
-
B.
causeOfPersecution
chosen
Indicates that one entity is the reason or basis for another entity being persecuted.
-
C.
censorshipYear
Indicates the year in which an act of censorship was imposed on the referenced content or entity.
-
D.
mediaFreedom
Indicates the degree to which media outlets can operate, report, and express information without censorship, interference, or undue restriction.
-
E.
canCensure
Indicates that one entity has the authority or power to formally reprimand, criticize, or express disapproval of another entity’s actions or behavior.
- 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_69a88b08e4308190bdac9aebcca1c91a |
completed | March 4, 2026, 7:42 p.m. |
| NER | Named-entity recognition | batch_69abc2194150819083156e4dcd45a423 |
completed | March 7, 2026, 6:13 a.m. |
| PD | Predicate disambiguation | batch_69abbdb9aa3c819088d0316c5269a1c2 |
completed | March 7, 2026, 5:55 a.m. |
Created at: March 4, 2026, 7:48 p.m.