Triple
T18730262
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | United States retail industry |
E458013
|
entity |
| Predicate | consumerTrend |
P39078
|
FINISHED |
| Object | growth of online shopping |
—
|
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: growth of online shopping | Statement: [United States retail industry, consumerTrend, growth of online shopping]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: consumerTrend Context triple: [United States retail industry, consumerTrend, growth of online shopping]
-
A.
trends
chosen
Indicates that one entity exhibits a general direction of change or development over time in relation to another reference or context.
-
B.
trendy
Indicates that something is currently fashionable, popular, or in line with prevailing styles or tastes.
-
C.
designTrend
Indicates a prevailing or emerging stylistic direction or pattern that influences how something is designed over a period of time.
-
D.
technologyTrend
Indicates a relationship where a technology is characterized as part of a broader pattern of change or direction in technological development over time.
-
E.
marketPreference
Indicates a relationship where one entity favors, targets, or prioritizes a particular market or market segment over others.
- 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_69d8d393ba9c8190a8b03b04ddbb0a09 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e56d778cf8819083500600b9ac0744 |
completed | April 20, 2026, 12:04 a.m. |
| PD | Predicate disambiguation | batch_69e48d03766c8190a43f7681842f4f8d |
completed | April 19, 2026, 8:06 a.m. |
Created at: April 10, 2026, 11:50 a.m.