Triple
T2004546
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Boris Godunov |
E43550
|
entity |
| Predicate | revisedVersionCensorshipStatus |
P35074
|
FINISHED |
| Object | approved by Imperial Theatres censors |
—
|
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: approved by Imperial Theatres censors | Statement: [Boris Godunov, revisedVersionCensorshipStatus, approved by Imperial Theatres censors]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: revisedVersionCensorshipStatus Context triple: [Boris Godunov, revisedVersionCensorshipStatus, approved by Imperial Theatres censors]
-
A.
hasCensorshipHistory
Indicates that an entity has previously been subject to censorship or involved in acts of censoring content.
-
B.
canCensure
Indicates that one entity has the authority or power to formally reprimand, criticize, or express disapproval of another entity’s actions or behavior.
-
C.
canonicalStatus
Indicates the formal or official standing of an entity within an established authoritative or normative system.
-
D.
legalStatusAfterCoup
Indicates the legal status or standing of an entity following a coup or unconstitutional change of power.
-
E.
CISStatus
Indicates the compliance or certification status of an entity with respect to CIS (Center for Internet Security) benchmarks or standards.
- F. None of above. chosen
Provenance (4 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_69a88715dbbc8190b2299e29e955d997 |
completed | March 4, 2026, 7:25 p.m. |
| NER | Named-entity recognition | batch_69abb89717c88190ba506134c671d386 |
completed | March 7, 2026, 5:33 a.m. |
| PD | Predicate disambiguation | batch_69abb79e63c08190982c8b44a557266f |
completed | March 7, 2026, 5:29 a.m. |
| PDg | Predicate description generation | batch_69abb87b9fc08190a748c278ef2d7dc7 |
completed | March 7, 2026, 5:32 a.m. |
Created at: March 4, 2026, 7:37 p.m.