Triple
T17911375
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Outlaw Star |
E447824
|
entity |
| Predicate | hasCensorshipInUSBroadcast |
P74007
|
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: [Outlaw Star, hasCensorshipInUSBroadcast, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCensorshipInUSBroadcast Context triple: [Outlaw Star, hasCensorshipInUSBroadcast, yes]
-
A.
wasCensored
chosen
Indicates that an entity’s content, expression, or communication was suppressed, altered, or restricted by an authority or controlling party.
-
B.
censorshipReason
Indicates the justification or cause given for why certain content is suppressed, restricted, or removed.
-
C.
censorshipLevel
Indicates the degree or strictness of control, suppression, or restriction applied to information, media, or expression.
-
D.
censoredSetting
Indicates that a setting or environment has been modified to restrict, remove, or obscure certain content or information.
-
E.
censorshipAuthority
Indicates that one entity has the official power or responsibility to censor, restrict, or approve the information, media, or expression of another entity.
- 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_69d8b9f6d394819082a6d69fd1e23d2f |
completed | April 10, 2026, 8:51 a.m. |
| NER | Named-entity recognition | batch_69e49ea0ea008190b54a999e0704fb67 |
completed | April 19, 2026, 9:21 a.m. |
| PD | Predicate disambiguation | batch_69e3d8ec2f6881909d7f54b878cbed37 |
completed | April 18, 2026, 7:18 p.m. |
Created at: April 10, 2026, 10:19 a.m.