Triple
T35804670
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Attitude Era |
E1035071
|
entity |
| Predicate | contentRatingTrend |
P140683
|
FINISHED |
| Object | more mature themes |
—
|
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: more mature themes | Statement: [Attitude Era, contentRatingTrend, more mature themes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: contentRatingTrend Context triple: [Attitude Era, contentRatingTrend, more mature themes]
-
A.
ratingTrend
chosen
Indicates how an entity’s rating changes over time, such as improving, declining, or remaining stable.
-
B.
ageRatingControversy
Indicates that there is a dispute, concern, or notable issue regarding the appropriateness or assignment of an age rating for something.
-
C.
hasContentRating
Indicates that something is associated with a specified content rating that reflects its suitability for particular audiences.
-
D.
ageRatingContext
Indicates the contextual basis or circumstances (such as region, system, or criteria) under which an age rating is assigned or interpreted.
-
E.
ratedFor
Indicates that an entity has been evaluated and assigned a suitability or quality level for a particular purpose, context, or audience.
- 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_69f76e169bd081909f16cd8c9ee7870c |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69fba78aca4c8190b8f1831e8cc04e06 |
completed | May 6, 2026, 8:41 p.m. |
| PD | Predicate disambiguation | batch_69fba34a65a4819088bac6c17542d71c |
completed | May 6, 2026, 8:23 p.m. |
Created at: May 3, 2026, 4:06 p.m.