Triple
T18888327
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The First Nudie Musical |
E462014
|
entity |
| Predicate | targetRating |
P59739
|
FINISHED |
| Object | X-rated within the film's story |
—
|
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: X-rated within the film's story | Statement: [The First Nudie Musical, targetRating, X-rated within the film's story]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: targetRating Context triple: [The First Nudie Musical, targetRating, X-rated within the film's story]
-
A.
ratingCategory
Indicates the qualitative classification or level assigned to a rating (e.g., low, medium, high) within an evaluation or scoring system.
-
B.
targetAudienceRatingContext
Indicates the contextual conditions or setting (such as platform, region, or usage scenario) under which a particular audience rating is intended to apply.
-
C.
hasRatingLevel
chosen
Indicates that an entity is associated with a particular rating level or score category.
-
D.
usesRating
Indicates that one entity applies, relies on, or incorporates a rating assigned to another entity.
-
E.
ratingContext
Indicates the situational or contextual factors under which a rating is given or applies.
- 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_69d8dcfc3430819095ee6fc0eb4c06a5 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5c478d8c481909291e7c471e5095a |
completed | April 20, 2026, 6:15 a.m. |
| PD | Predicate disambiguation | batch_69e4a2e27e1481908a8da10b28f07875 |
completed | April 19, 2026, 9:39 a.m. |
Created at: April 10, 2026, 11:58 a.m.