Triple
T33750574
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Intimate Moments for a Sensual Evening |
E864829
|
entity |
| Predicate | containsAdultLanguage |
P37187
|
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: [Intimate Moments for a Sensual Evening, containsAdultLanguage, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: containsAdultLanguage Context triple: [Intimate Moments for a Sensual Evening, containsAdultLanguage, true]
-
A.
containsAdultContent
Indicates that the referenced item includes material intended for adults, such as explicit sexual, violent, or otherwise age-restricted content.
-
B.
adultStatus
Indicates that an entity has reached a recognized age or stage of maturity qualifying it as an adult in a given context.
-
C.
hasAdultRank
Indicates that an entity holds a status or position classified as an adult-level rank within a given system or hierarchy.
-
D.
isAdultCharacter
Indicates that a character has reached adulthood, typically meeting the age or maturity criteria defining an adult within the given context.
-
E.
containsProfanity
chosen
Indicates that the referenced content includes one or more profane, vulgar, or offensive expressions.
- 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_69f3498c35f881909df279ae4270f831 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_6a0045a7b4c081908e4dedabda7cf790 |
completed | May 10, 2026, 8:45 a.m. |
| PD | Predicate disambiguation | batch_6a0042b148a48190974b173f352e4b7f |
completed | May 10, 2026, 8:32 a.m. |
Created at: May 1, 2026, 1:45 a.m.