Triple
T36999667
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shiro Lolita |
E915315
|
entity |
| Predicate | fashionSubcultureOf |
P142344
|
FINISHED |
| Object | Lolita fashion |
—
|
NE NERFINISHED |
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: Lolita fashion | Statement: [Shiro Lolita, fashionSubcultureOf, Lolita fashion]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fashionSubcultureOf Context triple: [Shiro Lolita, fashionSubcultureOf, Lolita fashion]
-
A.
basedOnSubculture
chosen
Indicates that something is derived from, influenced by, or rooted in a particular subculture.
-
B.
fashionStyle
Indicates the characteristic way in which an entity dresses or presents themselves in terms of clothing and appearance.
-
C.
fashionCategory
Indicates the classification of an item into a specific fashion-related category or type (e.g., clothing, footwear, accessories).
-
D.
notableSubculture
Indicates that one entity is a significant or well-recognized subculture within the context or domain of the other entity.
-
E.
influencedSubculture
Indicates that one entity has had a shaping or significant impact on the development, style, or practices of a particular subculture.
- 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_69f76e8f1a8c81909db172ed31304971 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69fb34e5576881909394355c8ec6ddd2 |
completed | May 6, 2026, 12:32 p.m. |
| PD | Predicate disambiguation | batch_69fb2f6171e88190bf1e0ee6a644b6a9 |
completed | May 6, 2026, 12:09 p.m. |
Created at: May 3, 2026, 4:14 p.m.