Triple

T7027385
Position Surface form Disambiguated ID Type / Status
Subject Generalized Advantage Estimation E163182 entity
Predicate proposedBy P32 FINISHED
Object Pieter Abbeel E162135 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: Pieter Abbeel | Statement: [Generalized Advantage Estimation, proposedBy, Pieter Abbeel]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Pieter Abbeel
Context triple: [Generalized Advantage Estimation, proposedBy, Pieter Abbeel]
  • A. Pieter Abbeel chosen
    Pieter Abbeel is a Belgian-American computer scientist and professor at UC Berkeley known for his influential work in robotics and deep reinforcement learning.
  • B. Sergey Levine
    Sergey Levine is a prominent computer scientist and professor known for his influential research in deep reinforcement learning and robotics.
  • C. Dario Amodei
    Dario Amodei is an AI researcher and entrepreneur, co-founder and CEO of Anthropic and former OpenAI research leader known for his work on large language models and AI safety.
  • D. Nicolas Heess
    Nicolas Heess is a machine learning researcher known for his work in deep reinforcement learning, including contributions to algorithms such as Deep Deterministic Policy Gradient (DDPG).
  • E. Shane Legg
    Shane Legg is a computer scientist and AI researcher best known as a co-founder of DeepMind and for his influential work on artificial general intelligence.
  • 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_69c6885d691c81908cf7d31083113886 completed March 27, 2026, 1:38 p.m.
NER Named-entity recognition batch_69c6e1fee32081908eff988b18daa6d0 completed March 27, 2026, 8:01 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7943ca8548190877d2698265ce7da completed March 28, 2026, 8:41 a.m.
Created at: March 27, 2026, 2:35 p.m.