Triple
T17635864
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hussars |
E430090
|
entity |
| Predicate | uniformStyleInfluenced |
P8654
|
FINISHED |
| Object | European light cavalry fashion |
—
|
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: European light cavalry fashion | Statement: [Hussars, uniformStyleInfluenced, European light cavalry fashion]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: uniformStyleInfluenced Context triple: [Hussars, uniformStyleInfluenced, European light cavalry fashion]
-
A.
uniformStyle
Indicates that the related entities share the same or a consistent style, pattern, or formatting.
-
B.
styleTendsTo
Indicates that one style is generally inclined or likely to develop, appear, or be adopted in the direction of another style.
-
C.
usedStyle
Indicates that one entity employed or applied a particular style, method, or manner associated with another entity.
-
D.
inTheStyleOf
Indicates that one entity is created, performed, or presented in a manner that imitates or closely resembles the characteristic style of another entity.
-
E.
relatedStyle
chosen
Indicates that one style is associated with, similar to, or derived from another style in some relevant way.
- 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_69d889e37f308190a6aa0a69daff86c7 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e46de0ad988190b1a2c0bff69eb9f1 |
completed | April 19, 2026, 5:53 a.m. |
| PD | Predicate disambiguation | batch_69e3cddc87188190ac2f049b86038676 |
completed | April 18, 2026, 6:30 p.m. |
Created at: April 10, 2026, 5:52 a.m.