Triple
T804811
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Luke Nosek |
E17405
|
entity |
| Predicate | businessModelFocus |
P21224
|
FINISHED |
| Object | internet startups |
—
|
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: internet startups | Statement: [Luke Nosek, businessModelFocus, internet startups]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: businessModelFocus Context triple: [Luke Nosek, businessModelFocus, internet startups]
-
A.
businessModelPioneerOf
Indicates that an entity was the first or among the first to introduce, develop, or popularize a particular business model that others later adopted.
-
B.
brandFocus
Indicates that a brand primarily concentrates its efforts, messaging, or resources on a particular target, theme, or market segment.
-
C.
underlyingCompanyBusinessFocus
Indicates the primary industry, sector, or type of business activity that the underlying company is focused on.
-
D.
businessFunction
Indicates the specific role, activity, or operational function that an entity performs within a business context.
-
E.
usesBusinessModel
Indicates that one entity operates according to, or applies in practice, the business model defined or provided by another entity.
- F. None of above. chosen
Provenance (4 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_69a4937ae8a08190b5084a03d532b30e |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4ace495348190aec66f35ea90bc89 |
completed | March 1, 2026, 9:17 p.m. |
| PD | Predicate disambiguation | batch_69a4aa70973c8190adbf08302d1103a9 |
completed | March 1, 2026, 9:06 p.m. |
| PDg | Predicate description generation | batch_69a4ace369b481908ad69de6de99f5e6 |
completed | March 1, 2026, 9:17 p.m. |
Created at: March 1, 2026, 7:38 p.m.