Triple
T3239772
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Delirious |
E67938
|
entity |
| Predicate | containsAdultContent |
P47549
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Delirious, containsAdultContent, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: containsAdultContent Context triple: [Delirious, containsAdultContent, true]
-
A.
hasContentRating
Indicates that something is associated with a specified content rating that reflects its suitability for particular audiences.
-
B.
hasAdultRank
Indicates that an entity holds a status or position classified as an adult-level rank within a given system or hierarchy.
-
C.
hasAdultPrograms
Indicates that an entity offers or is associated with programs or services specifically designed for adults.
-
D.
depictsSex
Indicates that one entity visually represents or portrays sexual activity or sexual content involving another entity.
-
E.
containsProfanity
Indicates that the referenced content includes one or more profane, vulgar, or offensive expressions.
- 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_69ad858d27348190abb61c280b4c86a9 |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69adaef4c0bc819095e4f84296fe7cb6 |
completed | March 8, 2026, 5:16 p.m. |
| PD | Predicate disambiguation | batch_69ada4159e0481908cbbdd750f5e08c7 |
completed | March 8, 2026, 4:30 p.m. |
| PDg | Predicate description generation | batch_69ada698eeb48190a1f5762fdd3b7b63 |
completed | March 8, 2026, 4:40 p.m. |
Created at: March 8, 2026, 3:08 p.m.