Triple

T2330530
Position Surface form Disambiguated ID Type / Status
Subject Vincent Vanhoucke E48390 entity
Predicate affiliation P10 FINISHED
Object Google Brain E7923 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 Brain | Statement: [Vincent Vanhoucke, affiliation, Google Brain]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Google Brain
Context triple: [Vincent Vanhoucke, affiliation, Google Brain]
  • A. Google Brain chosen
    Google Brain is a deep learning research team at Google that pioneered many advances in neural networks and artificial intelligence.
  • B. Google Tensor
    Google Tensor is Google's custom-designed system-on-a-chip (SoC) platform created to power Pixel devices with advanced AI and machine learning capabilities.
  • C. DeepMind
    DeepMind is a leading artificial intelligence research company renowned for breakthroughs such as AlphaGo and deep reinforcement learning, operating as a subsidiary of Google.
  • D. Google Research
    Google Research is the research division of Google focused on advancing the state of the art in computer science and artificial intelligence through fundamental and applied research.
  • E. AlphaGo
    AlphaGo is an artificial intelligence program developed by DeepMind that became famous for defeating world champion Go players using deep neural networks and reinforcement learning.
  • 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_69a88aa308a88190b0b86c011fda7fce completed March 4, 2026, 7:40 p.m.
NER Named-entity recognition batch_69abc667235c819086140af9db961203 completed March 7, 2026, 6:32 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae96185a1c8190a115588f8a5b92f7 completed March 9, 2026, 9:42 a.m.
Created at: March 4, 2026, 7:50 p.m.