Triple
T36999699
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shiro Lolita |
E915315
|
entity |
| Predicate | becamePopularThrough |
P171669
|
FINISHED |
| Object | online Lolita communities |
—
|
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: online Lolita communities | Statement: [Shiro Lolita, becamePopularThrough, online Lolita communities]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: becamePopularThrough Context triple: [Shiro Lolita, becamePopularThrough, online Lolita communities]
-
A.
achievedPopularityVia
chosen
Indicates that an entity gained recognition or widespread acceptance through a particular method, channel, or means.
-
B.
achievedPopularityIn
Indicates that an entity became popular or widely recognized within a specified place, group, or context.
-
C.
gainedProminenceAs
Indicates that an entity became widely recognized or notable in the role, capacity, or identity specified by another entity.
-
D.
helpedPropelToMainstreamFame
Indicates that one entity significantly contributed to another entity’s rise to widespread public recognition or mainstream popularity.
-
E.
popularizedIn
Indicates that something became widely known, accepted, or fashionable within a particular place, time period, or 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_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.