Triple
T20739160
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mary Kay Ash |
E509791
|
entity |
| Predicate | industryOfCompanyFounded |
P59909
|
FINISHED |
| Object | cosmetics |
—
|
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: cosmetics | Statement: [Mary Kay Ash, industryOfCompanyFounded, cosmetics]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: industryOfCompanyFounded Context triple: [Mary Kay Ash, industryOfCompanyFounded, cosmetics]
-
A.
industryStart
Indicates the point in time or event at which an industry, industrial activity, or industrial era begins.
-
B.
targetCompanyIndustry
chosen
Indicates that a company operates within or is associated with a specified industry sector.
-
C.
foundedBusinessIn
Indicates that an entity established or started a business in a particular location or jurisdiction.
-
D.
foundedCompany
Indicates that an entity established or created a company, typically as its founder or co-founder.
-
E.
industryOfUnderlyingCompany
Indicates the industry sector in which the underlying company associated with this entity operates.
- 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_69e0b4c589c08190834fb5d86d0efa2b |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6c20d9d4c8190a2fd87f8a33c313d |
completed | April 21, 2026, 12:17 a.m. |
| PD | Predicate disambiguation | batch_69e5c0509608819080cdbf47fcddfe36 |
completed | April 20, 2026, 5:57 a.m. |
Created at: April 16, 2026, 12:32 p.m.