Triple

T8969397
Position Surface form Disambiguated ID Type / Status
Subject Bill Maris E214224 entity
Predicate employer P7 FINISHED
Object Google Ventures E184184 NE 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: Google Ventures | Statement: [Bill Maris, employer, Google Ventures]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Google Ventures
Context triple: [Bill Maris, 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. Sequoia Capital
    Sequoia Capital is a leading Silicon Valley venture capital firm known for early investments in companies like Apple, Google, and Airbnb.
  • D. Y Combinator
    Y Combinator is a prominent Silicon Valley startup accelerator known for funding and mentoring early-stage technology companies such as Airbnb, Dropbox, and Stripe.
  • E. Andreessen Horowitz
    Andreessen Horowitz is a prominent Silicon Valley venture capital firm known for backing leading technology startups across software, fintech, crypto, and other innovation-driven sectors.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

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_69ca839dbf608190a2f5990477115d29 completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cc6765babc8190a4a3b79aa21047c8 completed April 1, 2026, 12:31 a.m.
NED1 Entity disambiguation (via context triple) batch_69cfc96006e48190978e4ccdedc48b41 completed April 3, 2026, 2:06 p.m.
Created at: March 30, 2026, 7:01 p.m.