Triple
T13660963
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Contest |
E326991
|
entity |
| Predicate | networkCensorshipAvoidedExplicitWord |
P111035
|
FINISHED |
| Object | masturbation |
—
|
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: masturbation | Statement: [The Contest, networkCensorshipAvoidedExplicitWord, masturbation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: networkCensorshipAvoidedExplicitWord Context triple: [The Contest, networkCensorshipAvoidedExplicitWord, masturbation]
-
A.
wasCensored
Indicates that an entity’s content, expression, or communication was suppressed, altered, or restricted by an authority or controlling party.
-
B.
coCensorWith
Indicates that two or more entities participate together in the act of censoring the same content or subject.
-
C.
censorshipReason
Indicates the justification or cause given for why certain content is suppressed, restricted, or removed.
-
D.
censorshipLevel
Indicates the degree or strictness of control, suppression, or restriction applied to information, media, or expression.
-
E.
networkCensorshipIssues
Indicates that there are problems or restrictions in accessing content or services due to censorship imposed on a network.
- F. None of above. chosen
Provenance (4 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_69d8076d8270819092afc2f0e9c359a8 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbc620df208190afaccf3ddd10aa60 |
completed | April 12, 2026, 4:19 p.m. |
| PD | Predicate disambiguation | batch_69dbbe8a027081908d8f884b89707a5e |
completed | April 12, 2026, 3:47 p.m. |
| PDg | Predicate description generation | batch_69dbc59ca1a88190a6abd3bd00554c93 |
completed | April 12, 2026, 4:17 p.m. |
Created at: April 9, 2026, 9:52 p.m.