Triple
T20060382
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Move (Radio Edit) |
E499454
|
entity |
| Predicate | hasCensorship |
P104276
|
FINISHED |
| Object | profanity removed or obscured |
—
|
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: profanity removed or obscured | Statement: [Move (Radio Edit), hasCensorship, profanity removed or obscured]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCensorship Context triple: [Move (Radio Edit), hasCensorship, profanity removed or obscured]
-
A.
hasCensorshipHistory
Indicates that an entity has previously been subject to censorship or involved in acts of censoring content.
-
B.
wasCensored
Indicates that an entity’s content, expression, or communication was suppressed, altered, or restricted by an authority or controlling party.
-
C.
hasCensorshipControversy
Indicates that an entity has been involved in disputes, criticism, or public debate related to censorship of its content or activities.
-
D.
censorshipLevel
Indicates the degree or strictness of control, suppression, or restriction applied to information, media, or expression.
-
E.
censoredSetting
chosen
Indicates that a setting or environment has been modified to restrict, remove, or obscure certain content or information.
- 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_69da6276bcf48190aabbf279192a5fb4 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e66374f4a48190beb575a6c84ebdb4 |
completed | April 20, 2026, 5:33 p.m. |
| PD | Predicate disambiguation | batch_69e54cee7a5c819084ae4ff26419833f |
completed | April 19, 2026, 9:45 p.m. |
Created at: April 11, 2026, 3:38 p.m.