Triple
T6993278
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pieter Abbeel |
E162135
|
entity |
| Predicate | notableStudent |
P4838
|
FINISHED |
| Object | Sergey Levine |
E164770
|
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: Sergey Levine | Statement: [Pieter Abbeel, notableStudent, Sergey Levine]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sergey Levine Context triple: [Pieter Abbeel, notableStudent, Sergey Levine]
-
A.
Sergey Levine
chosen
Sergey Levine is a prominent computer scientist and professor known for his influential research in deep reinforcement learning and robotics.
-
B.
Pieter Abbeel
Pieter Abbeel is a Belgian-American computer scientist and professor at UC Berkeley known for his influential work in robotics and deep reinforcement learning.
-
C.
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).
-
D.
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.
-
E.
Ilya Sutskever
Ilya Sutskever is a leading artificial intelligence researcher and co-founder of OpenAI, known for his pioneering work in deep learning and neural networks.
- 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_69c68856d7808190ab33ee914640281b |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6dbc30fdc81909244d83c8178755c |
completed | March 27, 2026, 7:34 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c77551f85881909893d67176ee5556 |
completed | March 28, 2026, 6:29 a.m. |
Created at: March 27, 2026, 2:32 p.m.