Triple
T32285951
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Statues Also Die |
E824827
|
entity |
| Predicate | banPeriod |
P173929
|
FINISHED |
| Object | partially banned in France for several years after release |
—
|
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: partially banned in France for several years after release | Statement: [Statues Also Die, banPeriod, partially banned in France for several years after release]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: banPeriod Context triple: [Statues Also Die, banPeriod, partially banned in France for several years after release]
-
A.
banPeriodStart
Indicates the date or time at which a ban or prohibition begins to take effect.
-
B.
banPeriodEnd
Indicates the point in time when a ban or prohibition on an entity or action is scheduled to end.
-
C.
bannedAfter
Indicates that one entity becomes prohibited or forbidden only after the occurrence or establishment of another specified entity or event.
-
D.
suspensionPeriod
Indicates the time span during which a right, service, or status is temporarily inactive or halted.
-
E.
banType
Indicates the specific category or kind of prohibition or restriction that has been applied.
- 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_69f349101b788190b4f14884dc7d1ed2 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f6bccf68b0819096225377b8130beb |
completed | May 3, 2026, 3:11 a.m. |
| PD | Predicate disambiguation | batch_69f6b632cf788190a3d0c08cd026b84b |
completed | May 3, 2026, 2:42 a.m. |
| PDg | Predicate description generation | batch_69f6b960ca4081909a77690c2b122f5e |
completed | May 3, 2026, 2:56 a.m. |
Created at: May 1, 2026, 12:43 a.m.