Triple
T2359103
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Red Pill communities |
E47229
|
entity |
| Predicate | framesGenderRelationsAs |
P23406
|
FINISHED |
| Object | power struggle |
—
|
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: power struggle | Statement: [Red Pill communities, framesGenderRelationsAs, power struggle]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: framesGenderRelationsAs Context triple: [Red Pill communities, framesGenderRelationsAs, power struggle]
-
A.
hasTypicalGenderAssociation
Indicates that one entity is commonly or culturally associated with a particular gender more than with other genders.
-
B.
associatedPatriarchate
Indicates a relationship where an entity is linked or connected to a particular patriarchate as its religious or ecclesiastical authority.
-
C.
hasGenderFocus
Indicates that something is specifically concerned with, oriented toward, or primarily addressing a particular gender or gender-related issues.
-
D.
genderStereotypingRecognizedAs
Indicates that a particular belief, behavior, or representation is acknowledged or classified as a form of gender stereotyping.
-
E.
portraysRelationship
chosen
Indicates that one entity depicts, represents, or illustrates a relationship between other entities.
- 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_69a88a1a4a6081908645b0f2914521ab |
completed | March 4, 2026, 7:38 p.m. |
| NER | Named-entity recognition | batch_69abc720b9048190a5d3b19e5e1f373a |
completed | March 7, 2026, 6:35 a.m. |
| PD | Predicate disambiguation | batch_69abc599b92c819093d9e15d4437705d |
completed | March 7, 2026, 6:28 a.m. |
Created at: March 4, 2026, 7:55 p.m.