Triple
T23250398
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yeehaw Challenge |
E581715
|
entity |
| Predicate | trendType |
P70527
|
FINISHED |
| Object | fashion trend |
—
|
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: fashion trend | Statement: [Yeehaw Challenge, trendType, fashion trend]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: trendType Context triple: [Yeehaw Challenge, trendType, fashion trend]
-
A.
trends
Indicates that one entity exhibits a general direction of change or development over time in relation to another reference or context.
-
B.
hasTrend
Indicates that something exhibits or is associated with a particular pattern of change or direction over time.
-
C.
trendy
Indicates that something is currently fashionable, popular, or in line with prevailing styles or tastes.
-
D.
hasOnlineTrendType
chosen
Indicates that an entity is associated with a specific category or type of online trend.
-
E.
continuedTrend
Indicates that a previously observed pattern or direction in some variable or behavior persists over a subsequent time period without significant change.
- 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_69e24606b17c81908aba1a4911c8a8ba |
completed | April 17, 2026, 2:39 p.m. |
| NER | Named-entity recognition | batch_69f193f5aa9081909775fb7f7dc660b3 |
completed | April 29, 2026, 5:15 a.m. |
| PD | Predicate disambiguation | batch_69effce4d704819092826931d430e8c4 |
completed | April 28, 2026, 12:18 a.m. |
Created at: April 17, 2026, 4:10 p.m.