Triple
T13036152
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kima Ventures |
E326564
|
entity |
| Predicate | portfolioCompaniesCount |
P17464
|
FINISHED |
| Object | hundreds |
—
|
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: hundreds | Statement: [Kima Ventures, portfolioCompaniesCount, hundreds]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: portfolioCompaniesCount Context triple: [Kima Ventures, portfolioCompaniesCount, hundreds]
-
A.
portfolioCompany
Indicates that one entity is a company in which another entity (typically an investor or investment fund) holds an ownership stake as part of its investment portfolio.
-
B.
hasNumberOfCompanies
chosen
Indicates the quantitative relationship specifying how many companies are associated with a given entity.
-
C.
targetCompanies
Indicates that certain companies are the intended focus or recipients of a particular action, effort, or objective.
-
D.
hasCompanyName
Indicates that an entity is associated with or identified by a specific company name.
-
E.
companyIncorporatedIn
Indicates that a company was legally formed and registered in a specified jurisdiction or location.
- 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_69d8076cc45c81908123123f43e69266 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69d97f2a71a0819098bb6cf8a4b2208a |
completed | April 10, 2026, 10:52 p.m. |
| PD | Predicate disambiguation | batch_69d97dc39a0881908119c62e31bf6182 |
completed | April 10, 2026, 10:46 p.m. |
Created at: April 9, 2026, 8:55 p.m.