Triple
T2415208
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Last Tango in Paris |
E52285
|
entity |
| Predicate | laterRating |
P13710
|
FINISHED |
| Object | NC-17 |
—
|
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: NC-17 | Statement: [Last Tango in Paris, laterRating, NC-17]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: laterRating Context triple: [Last Tango in Paris, laterRating, NC-17]
-
A.
rating
Indicates an evaluation relationship where one entity assigns a qualitative or quantitative score or judgment to another entity.
-
B.
ratingDescription
Indicates the textual explanation or qualitative summary associated with a given rating or score.
-
C.
laterStatus
chosen
Indicates that one entity represents a subsequent or resulting status or condition of another entity in time.
-
D.
ratingExpectation
Indicates an anticipated or predicted evaluation score that one entity expects another entity to receive or assign.
-
E.
ratingSystem
Indicates a system or method used to assign evaluative scores or rankings to items, actions, or entities based on defined criteria.
- 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.