Triple
T2415221
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Last Tango in Paris |
E52285
|
entity |
| Predicate | hasFilmRatingControversy |
P1783
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Last Tango in Paris, hasFilmRatingControversy, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFilmRatingControversy Context triple: [Last Tango in Paris, hasFilmRatingControversy, yes]
-
A.
hasContentRating
Indicates that something is associated with a specified content rating that reflects its suitability for particular audiences.
-
B.
roleInControversy
Indicates the specific part, involvement, or function an entity has within a particular controversy or disputed situation.
-
C.
controversy
chosen
Indicates a situation in which there is active disagreement, dispute, or public debate between parties over a particular issue, action, or claim.
-
D.
hasFilmRatingAustralia
Indicates that an entity (typically a film or audiovisual work) has a specific official classification or rating assigned by the Australian film rating system.
-
E.
hasNotableCritic
Indicates that one entity serves as a significant or widely recognized critic 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_69ab495622948190bc6bc6e4cddaf645 |
completed | March 6, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69abc94bd7ec81909f5b4a16a406165b |
completed | March 7, 2026, 6:44 a.m. |
| PD | Predicate disambiguation | batch_69abc5a6cbd0819086c0716e266b7ebb |
completed | March 7, 2026, 6:28 a.m. |
Created at: March 6, 2026, 9:41 p.m.