Triple

T11003639
Position Surface form Disambiguated ID Type / Status
Subject Neural Turing Machines E260059 entity
Predicate hasContributor P4244 FINISHED
Object DeepMind E6331 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: DeepMind | Statement: [Neural Turing Machines, hasContributor, DeepMind]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: DeepMind
Context triple: [Neural Turing Machines, hasContributor, DeepMind]
  • A. DeepMind chosen
    DeepMind is a leading artificial intelligence research company renowned for breakthroughs such as AlphaGo and deep reinforcement learning, operating as a subsidiary of Google.
  • B. 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.
  • C. Google Brain
    Google Brain is a deep learning research team at Google that pioneered many advances in neural networks and artificial intelligence.
  • D. AlphaStar
    AlphaStar is a DeepMind-created artificial intelligence system that achieved grandmaster-level performance in the real-time strategy game StarCraft II.
  • E. OpenAI
    OpenAI is an artificial intelligence research organization best known for developing advanced AI models such as ChatGPT and GPT series.
  • 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_69d6aa8a6a548190a750f944ccdc8064 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d797553c408190b8dca21250243479 completed April 9, 2026, 12:11 p.m.
NED1 Entity disambiguation (via context triple) batch_69e3a97587708190bf31976a3fbc1015 completed April 18, 2026, 3:55 p.m.
Created at: April 8, 2026, 9:25 p.m.