Triple
T27988313
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Les Amants |
E706803
|
entity |
| Predicate | censorshipControversyIn |
P139795
|
FINISHED |
| Object | United States |
—
|
NE NERFINISHED |
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: United States | Statement: [Les Amants, censorshipControversyIn, United States]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: censorshipControversyIn Context triple: [Les Amants, censorshipControversyIn, United States]
-
A.
hasCensorshipControversy
Indicates that an entity has been involved in disputes, criticism, or public debate related to censorship of its content or activities.
-
B.
censorshipIssues
Indicates that one entity imposes restrictions, suppression, or control over the information, expression, or content associated with another entity.
-
C.
countryOfCensorshipControversy
chosen
Indicates the country in which a particular censorship-related controversy or dispute took place.
-
D.
censorshipEvent
Indicates an event in which information, expression, or communication is suppressed, restricted, or altered by some controlling authority or mechanism.
-
E.
censorshipConsequence
Indicates the outcome or impact that results from an act or policy of censorship being applied.
- 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_69ef96b8b8d88190bad5e4ae966bf14e |
completed | April 27, 2026, 5:02 p.m. |
| NER | Named-entity recognition | batch_69f63b6f14508190afdf5fc4aa04e855 |
completed | May 2, 2026, 5:59 p.m. |
| PD | Predicate disambiguation | batch_69f63710d17c819084cfe96e6df334fd |
completed | May 2, 2026, 5:40 p.m. |
Created at: April 27, 2026, 7:48 p.m.