Triple
T18301451
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Joe Kraus |
E438365
|
entity |
| Predicate | employer |
P7
|
FINISHED |
| Object | Google Ventures |
—
|
NE NERFINISHED |
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: Google Ventures | Statement: [Joe Kraus, employer, Google Ventures]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Google Ventures Context triple: [Joe Kraus, employer, Google Ventures]
-
A.
Google Ventures
chosen
Google Ventures is the venture capital investment arm of Alphabet Inc., focused on funding and supporting early-stage technology and life sciences startups.
-
B.
Khosla Ventures
Khosla Ventures is a Silicon Valley-based venture capital firm known for investing in early-stage, high-risk technology and clean energy startups.
-
C.
500 Startups
500 Startups is a global venture capital firm and startup accelerator known for investing in and mentoring early-stage technology companies around the world.
-
D.
Sequoia Capital
Sequoia Capital is a leading Silicon Valley venture capital firm known for early investments in companies like Apple, Google, and Airbnb.
-
E.
Union Square Ventures
Union Square Ventures is a New York–based venture capital firm known for early-stage investments in prominent internet and technology companies.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8b915e3e881909125d760c15d0c29 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e5017f63dc819083a675d570620f2f |
completed | April 19, 2026, 4:23 p.m. |
Created at: April 10, 2026, 10:35 a.m.