Triple
T1946257
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lezginka (Azerbaijani variant) |
E42060
|
entity |
| Predicate | typicalGenderRoles |
P18942
|
FINISHED |
| Object | male lead with virtuosic steps |
—
|
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: male lead with virtuosic steps | Statement: [Lezginka (Azerbaijani variant), typicalGenderRoles, male lead with virtuosic steps]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalGenderRoles Context triple: [Lezginka (Azerbaijani variant), typicalGenderRoles, male lead with virtuosic steps]
-
A.
genderStereotypingRecognizedAs
Indicates that a particular belief, behavior, or representation is acknowledged or classified as a form of gender stereotyping.
-
B.
genderCategories
Indicates the classification of an entity into one or more gender-related categories or identities.
-
C.
hasGenderInSomeTraditions
Indicates that, in at least some cultural, religious, or historical traditions, the subject is regarded as having a specific gender.
-
D.
typicalRole
chosen
Indicates that one entity serves as the usual, characteristic, or commonly expected role or function of another entity.
-
E.
genderRule
Indicates a rule or constraint that determines how gender-related properties or classifications should be assigned or interpreted in a given context.
- 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_69a8870e08fc8190a319cbf2600db15f |
completed | March 4, 2026, 7:25 p.m. |
| NER | Named-entity recognition | batch_69abb32ebae881908f7541301f0198ae |
completed | March 7, 2026, 5:10 a.m. |
| PD | Predicate disambiguation | batch_69abaff25a588190bb4cbc8df9fc6d64 |
completed | March 7, 2026, 4:56 a.m. |
Created at: March 4, 2026, 7:36 p.m.