Bilal Piot
E736833
Bilal Piot is a machine learning researcher known for his contributions to deep reinforcement learning, including co-authoring the Rainbow DQN algorithm.
All labels observed (1)
| Label | Occurrences |
|---|---|
| Bilal Piot canonical | 2 |
How this entity was disambiguated
This entity first appeared as the object of triple T8482977 — resolving that mention is where its identity was fixed. The disambiguator weighed these candidate entities and picked the highlighted one (or “None”, minting a new entity). This is how homonymy is resolved: the same surface form can point to different entities.
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bilal Piot Context triple: [Rainbow DQN, proposedBy, Bilal Piot]
-
A.
Patrick Baladi
Patrick Baladi is a British actor best known for his television roles in series such as The Office (UK), Mistresses, and Line of Duty.
-
B.
Bilal
Bilal is an American neo-soul and R&B singer-songwriter known for his rich, genre-blending vocals and critically acclaimed work with artists across hip-hop, jazz, and soul.
-
C.
Amar Khalil
Amar Khalil is an American R&B singer best known for his work with the influential Oakland-based group Tony! Toni! Toné!.
-
D.
Sami Bouajila
Sami Bouajila is a French-Tunisian actor acclaimed for his intense, nuanced performances in European cinema and international thrillers.
-
E.
Jamel Irief
Jamel Irief is the birth name of Masta Killa, an American rapper best known as a member of the influential hip hop group Wu-Tang Clan.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Bilal Piot Target entity description: Bilal Piot is a machine learning researcher known for his contributions to deep reinforcement learning, including co-authoring the Rainbow DQN algorithm.
-
A.
Patrick Baladi
Patrick Baladi is a British actor best known for his television roles in series such as The Office (UK), Mistresses, and Line of Duty.
-
B.
Bilal
Bilal is an American neo-soul and R&B singer-songwriter known for his rich, genre-blending vocals and critically acclaimed work with artists across hip-hop, jazz, and soul.
-
C.
Amar Khalil
Amar Khalil is an American R&B singer best known for his work with the influential Oakland-based group Tony! Toni! Toné!.
-
D.
Sami Bouajila
Sami Bouajila is a French-Tunisian actor acclaimed for his intense, nuanced performances in European cinema and international thrillers.
-
E.
Jamel Irief
Jamel Irief is the birth name of Masta Killa, an American rapper best known as a member of the influential hip hop group Wu-Tang Clan.
- F. None of above. chosen
Statements (41)
| Predicate | Object |
|---|---|
| instanceOf |
deep reinforcement learning algorithm
ⓘ
machine learning researcher ⓘ person ⓘ scientific paper ⓘ |
| basedOn |
Deep Q-Networks
ⓘ
linked to:
Deep Q-Learning
|
| coAuthorOf |
Rainbow: Combining Improvements in Deep Reinforcement Learning
ⓘ
linked to:
Rainbow DQN
|
| combines |
distributional reinforcement learning
ⓘ
double Q-learning ⓘ dueling network architectures ⓘ multi-step learning ⓘ noisy networks for exploration ⓘ prioritized experience replay ⓘ |
| contributedTo |
Rainbow DQN algorithm
ⓘ
linked to:
Rainbow DQN
|
| fieldOfWork |
artificial intelligence
ⓘ
deep reinforcement learning ⓘ machine learning ⓘ reinforcement learning ⓘ |
| hasAcademicBackgroundIn | computer science ⓘ |
| hasAuthor | Bilal Piot ⓘ |
| hasCoAuthor |
Dan Horgan
ⓘ
David Silver ⓘ Georg Ostrovski ⓘ Hado van Hasselt ⓘ Joseph Modayil ⓘ Matteo Hessel ⓘ Tom Schaul ⓘ Will Dabney ⓘ other Rainbow DQN collaborators ⓘ |
| hasResearchInterest |
deep Q-learning
ⓘ
exploration in reinforcement learning ⓘ off-policy reinforcement learning ⓘ value-based reinforcement learning ⓘ |
| knownFor |
Rainbow DQN
ⓘ
deep reinforcement learning research ⓘ |
| nationality | French ⓘ |
| publishedIn |
ICLR
ⓘ
ICML ⓘ NeurIPS ⓘ major machine learning conferences ⓘ |
| worksOn |
deep learning for control
ⓘ
scalable reinforcement learning algorithms ⓘ |
How these facts were elicited
The pipeline generated the facts above by prompting gpt-5.1 with this entity's name + description and the instruction below.
Instruction
You are a knowledge base construction expert. Given a subject entity and a description of it, return factual statements that you know for the subject as a JSON list of dictionaries(triples), where keys must be "subject", "predicate" and "object". The number of facts may be very high, between 25 to 50 or more, for very popular subjects. For less popular subjects, the number of facts can be very low, like 5 or 10. # Requirements - If you don't know the subject at all, return an empty list. - If the subject is not a named entity, return an empty list. - Include at least one triple where predicate is "instanceOf". - Do not get too wordy. - Separate several objects into multiple triples with one object.
Input
Subject: Bilal Piot Description of subject: Bilal Piot is a machine learning researcher known for his contributions to deep reinforcement learning, including co-authoring the Rainbow DQN algorithm.
Referenced by (2)
Full triples — surface form annotated when it differs from this entity's canonical label.
subject linked to:
Bilal Piot