Triple
T17749109
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Raise the Red Lantern |
E443066
|
entity |
| Predicate | censorshipStatusInChina |
P66015
|
FINISHED |
| Object | initially banned |
—
|
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: initially banned | Statement: [Raise the Red Lantern, censorshipStatusInChina, initially banned]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: censorshipStatusInChina Context triple: [Raise the Red Lantern, censorshipStatusInChina, initially banned]
-
A.
censorshipLevel
chosen
Indicates the degree or strictness of control, suppression, or restriction applied to information, media, or expression.
-
B.
censorshipIssues
Indicates that one entity imposes restrictions, suppression, or control over the information, expression, or content associated with another entity.
-
C.
legalStatusInChina
Indicates the legal status or standing that an entity holds under the laws and regulations of China.
-
D.
revisedVersionCensorshipStatus
Indicates the censorship or restriction status applied to a revised version of some original content.
-
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_69d8b9ed3a2081909b2ec0d4dd2f4c37 |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e48418c0188190beb31809b40e4648 |
completed | April 19, 2026, 7:28 a.m. |
| PD | Predicate disambiguation | batch_69e3cde9dc288190af0e2198487f2051 |
completed | April 18, 2026, 6:31 p.m. |
Created at: April 10, 2026, 10:10 a.m.