Triple
T28906344
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MILF of the Year |
E733091
|
entity |
| Predicate | targetsDemographicCategory |
P10541
|
FINISHED |
| Object | MILF performers |
—
|
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: MILF performers | Statement: [MILF of the Year, targetsDemographicCategory, MILF performers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: targetsDemographicCategory Context triple: [MILF of the Year, targetsDemographicCategory, MILF performers]
-
A.
targetedPopulation
Indicates the group of individuals or entities that an action, intervention, or effect is specifically directed toward.
-
B.
hasDemographic
Indicates that an entity is associated with or characterized by a particular demographic group or attribute.
-
C.
targetsGroup
chosen
Indicates that an action, influence, or effect is directed toward a specific group as its intended recipient or focus.
-
D.
targetQualification
Indicates that one entity specifies or defines the required qualification or eligibility criteria for another entity.
-
E.
demographicsLabel
Indicates the categorical demographic group or segment that an entity is associated with or classified under.
- 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_69f7cec454a88190a9f3bbee2b856636 |
completed | May 3, 2026, 10:40 p.m. |
| PD | Predicate disambiguation | batch_69f7c8977c288190997a892ec5f756ed |
completed | May 3, 2026, 10:13 p.m. |
Created at: April 28, 2026, 8:07 a.m.