Triple
T7074100
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sergey Levine |
E164770
|
entity |
| Predicate | hasAcademicAdvisor |
P167
|
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: [Sergey Levine, hasAcademicAdvisor, Pieter Abbeel]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Pieter Abbeel Context triple: [Sergey Levine, hasAcademicAdvisor, 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_69c6887b96548190a8a9b3ac8adf4119 |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e4ccb42c81909f5627aa97db7a84 |
completed | March 27, 2026, 8:13 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c79c8ca5a48190bbfbf640fb1f778d |
completed | March 28, 2026, 9:17 a.m. |
Created at: March 27, 2026, 2:39 p.m.