Triple
T38634378
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | No Russian |
E937538
|
entity |
| Predicate | contentRatingImpact |
P193041
|
FINISHED |
| Object | contributed to stricter scrutiny of violent content in games |
—
|
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: contributed to stricter scrutiny of violent content in games | Statement: [No Russian, contentRatingImpact, contributed to stricter scrutiny of violent content in games]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: contentRatingImpact Context triple: [No Russian, contentRatingImpact, contributed to stricter scrutiny of violent content in games]
-
A.
contentRatingBody
Indicates which organization or authority assigned the content rating for the item.
-
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.
ratingImpact
Indicates how one entity’s rating influences, changes, or determines the rating of another entity.
-
E.
ageRatingContext
Indicates the contextual basis or circumstances (such as region, system, or criteria) under which an age rating is assigned or interpreted.
- 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_69f76ed5ca3c81909288f61fbf37b359 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fd35d108908190b79b1e8e6bbd62aa |
completed | May 8, 2026, 1:01 a.m. |
| PD | Predicate disambiguation | batch_69fd34cb46108190b43c3b7f67ec4cd4 |
completed | May 8, 2026, 12:56 a.m. |
| PDg | Predicate description generation | batch_69fd35d029588190a525aa8a506e7708 |
completed | May 8, 2026, 1:01 a.m. |
Created at: May 3, 2026, 4:32 p.m.