Triple
T19755730
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lust |
E474494
|
entity |
| Predicate | targetOfCensorshipDebate |
P133958
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Lust, targetOfCensorshipDebate, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: targetOfCensorshipDebate Context triple: [Lust, targetOfCensorshipDebate, true]
-
A.
censorshipIssues
Indicates that one entity imposes restrictions, suppression, or control over the information, expression, or content associated with another entity.
-
B.
hasCensorshipControversy
chosen
Indicates that an entity has been involved in disputes, criticism, or public debate related to censorship of its content or activities.
-
C.
censorshipReason
Indicates the justification or cause given for why certain content is suppressed, restricted, or removed.
-
D.
censorshipEvent
Indicates an event in which information, expression, or communication is suppressed, restricted, or altered by some controlling authority or mechanism.
-
E.
censorshipLevel
Indicates the degree or strictness of control, suppression, or restriction applied to information, media, or expression.
- 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_69d8e51940a0819087bd2996f98da668 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e6531afcbc8190bd5364700008f6d8 |
completed | April 20, 2026, 4:23 p.m. |
| PD | Predicate disambiguation | batch_69e5305016e08190b9561a96baecb0b8 |
completed | April 19, 2026, 7:43 p.m. |
Created at: April 10, 2026, 1:48 p.m.