Triple
T20609189
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | She Bop |
E506398
|
entity |
| Predicate | censorshipLabel |
P138544
|
FINISHED |
| Object | PMRC target list |
—
|
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: PMRC target list | Statement: [She Bop, censorshipLabel, PMRC target list]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: censorshipLabel Context triple: [She Bop, censorshipLabel, PMRC target list]
-
A.
censorshipLevel
Indicates the degree or strictness of control, suppression, or restriction applied to information, media, or expression.
-
B.
censorshipTarget
chosen
Indicates that an entity is the object or focus of censorship by another entity or authority.
-
C.
censorshipReason
Indicates the justification or cause given for why certain content is suppressed, restricted, or removed.
-
D.
censorshipIssues
Indicates that one entity imposes restrictions, suppression, or control over the information, expression, or content associated with another entity.
-
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_69e0b4bb2b4081908fa4a72444120f35 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6aad5e53c8190b0add34ce9b31d57 |
completed | April 20, 2026, 10:38 p.m. |
| PD | Predicate disambiguation | batch_69e5a00c43308190b7ea58d559257e07 |
completed | April 20, 2026, 3:39 a.m. |
Created at: April 16, 2026, 11:41 a.m.