Triple
T28906351
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MILF of the Year |
E733091
|
entity |
| Predicate | isIntendedForAudience |
P102642
|
FINISHED |
| Object | adults |
—
|
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: adults | Statement: [MILF of the Year, isIntendedForAudience, adults]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isIntendedForAudience Context triple: [MILF of the Year, isIntendedForAudience, adults]
-
A.
isAudienceChoiceFor
Indicates that one entity represents a choice, option, or selection available to an audience in relation to another entity.
-
B.
isIntendedForUseBy
Indicates that something is designed, meant, or purposed to be used by a particular entity or group.
-
C.
intendedForAgeGroup
chosen
Indicates that something is designed, suitable, or targeted for use by a specific age group.
-
D.
isSuitableFor
Indicates that one entity is appropriate, fitting, or well-matched for use, application, or association with another entity.
-
E.
hasTargetAudienceLanguage
Indicates that something is intended for or directed toward an audience that speaks a particular language.
- 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_69f05b096d208190958a57d2e4b5a93a |
completed | April 28, 2026, 7 a.m. |
| NER | Named-entity recognition | batch_69f676f968d08190a4adba0439b438c9 |
completed | May 2, 2026, 10:13 p.m. |
| PD | Predicate disambiguation | batch_69f675ff62c48190a634bbb8896973b9 |
completed | May 2, 2026, 10:09 p.m. |
Created at: April 28, 2026, 8:07 a.m.