Triple
T15522999
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chuvash national costume |
E369013
|
entity |
| Predicate | genderVariation |
P119012
|
FINISHED |
| Object | men's costume |
—
|
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: men's costume | Statement: [Chuvash national costume, genderVariation, men's costume]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: genderVariation Context triple: [Chuvash national costume, genderVariation, men's costume]
-
A.
genderVariant
Indicates that an entity’s gender identity or expression differs from traditional or expected norms associated with their assigned sex or gender.
-
B.
genderReversalOf
Indicates that one entity is a counterpart of another with the same role or characteristics but with the opposite gender.
-
C.
hasGenderIdentity
Indicates that an entity identifies with or experiences a particular gender.
-
D.
genderConfiguration
Indicates how the genders of the involved entities are arranged or combined within a particular relationship or context.
-
E.
genderCategories
Indicates the classification of an entity into one or more gender-related categories or identities.
- F. None of above. chosen
Provenance (4 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_69d85a1794cc8190b0b428716296e63e |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e04143bda08190a2dee44918c1ad1c |
completed | April 16, 2026, 1:54 a.m. |
| PD | Predicate disambiguation | batch_69ded28ab0588190a47a9090d1238707 |
completed | April 14, 2026, 11:49 p.m. |
| PDg | Predicate description generation | batch_69ded57165288190979b7acb71ad5145 |
completed | April 15, 2026, 12:01 a.m. |
Created at: April 10, 2026, 4:04 a.m.