Triple
T30760900
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lezghinka |
E783230
|
entity |
| Predicate | typicalFemaleStyle |
P118808
|
FINISHED |
| Object | graceful |
—
|
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: graceful | Statement: [Lezghinka, typicalFemaleStyle, graceful]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalFemaleStyle Context triple: [Lezghinka, typicalFemaleStyle, graceful]
-
A.
correspondingFemaleStyle
chosen
Indicates that one style is the female or feminine counterpart of another style.
-
B.
fashionStyle
Indicates the characteristic way in which an entity dresses or presents themselves in terms of clothing and appearance.
-
C.
personHasNotableStyle
Indicates that a person is recognized for having a distinctive or noteworthy style.
-
D.
fashionCharacteristic
Indicates a relationship where one entity possesses or exhibits a particular style, trend, or fashion-related attribute in relation to another.
-
E.
typicalWear
Indicates that one entity is commonly or characteristically worn by the other in typical situations or contexts.
- 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_69f224b047f48190b4f5efeb7ee97b37 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_6a037c876524819098545e6037d3107d |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a0379e2fac0819089b522db3260028c |
completed | May 12, 2026, 7:05 p.m. |
Created at: April 29, 2026, 8:39 p.m.