Triple
T17693915
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alexander Pritzel |
E441108
|
entity |
| Predicate | coAuthorWith |
P398
|
FINISHED |
| Object | Nicolas Heess |
—
|
NE NERFINISHED |
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: Nicolas Heess | Statement: [Alexander Pritzel, coAuthorWith, Nicolas Heess]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nicolas Heess Context triple: [Alexander Pritzel, coAuthorWith, Nicolas Heess]
-
A.
Nicolas Heess
chosen
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).
-
B.
Martin Heusel
Martin Heusel is a researcher in machine learning best known for co-introducing the Fréchet Inception Distance (FID), a widely used metric for evaluating generative models.
-
C.
Ilya Goodfellow
Ilya Goodfellow is a machine learning researcher best known for inventing Generative Adversarial Networks (GANs) and contributing to deep learning at organizations like Google and OpenAI.
-
D.
Julian Schrittwieser
Julian Schrittwieser is a computer scientist and AI researcher known for his work at DeepMind on advanced reinforcement learning and game-playing systems such as AlphaZero.
-
E.
Sergey Levine
Sergey Levine is a prominent computer scientist and professor known for his influential research in deep reinforcement learning and robotics.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8b9e940b081908b862bb0e6e89b0d |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e4715485d88190b9b6f347ff85d7c7 |
completed | April 19, 2026, 6:08 a.m. |
Created at: April 10, 2026, 10:04 a.m.