Triple
T7166347
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Deep Throat Part II |
E167077
|
entity |
| Predicate | hasPornographicContent |
P47549
|
FINISHED |
| Object | false |
—
|
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: false | Statement: [Deep Throat Part II, hasPornographicContent, false]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPornographicContent Context triple: [Deep Throat Part II, hasPornographicContent, false]
-
A.
containsAdultContent
chosen
Indicates that the referenced item includes material intended for adults, such as explicit sexual, violent, or otherwise age-restricted content.
-
B.
hasContentRating
Indicates that something is associated with a specified content rating that reflects its suitability for particular audiences.
-
C.
hasNSFWPolicy
Indicates that an entity has an established policy governing the handling, display, or treatment of not-safe-for-work (NSFW) content.
-
D.
containsProfanity
Indicates that the referenced content includes one or more profane, vulgar, or offensive expressions.
-
E.
depictsSex
Indicates that one entity visually represents or portrays sexual activity or sexual content involving another entity.
- 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_69c68888c10c819095e0383020225758 |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e85a07388190a07054ef12870fa1 |
completed | March 27, 2026, 8:28 p.m. |
| PD | Predicate disambiguation | batch_69c6e1cd5c948190a9113b23f7308c21 |
completed | March 27, 2026, 8 p.m. |
Created at: March 27, 2026, 2:48 p.m.