Difference between revisions of "Neural Coreference"
| Line 3: | Line 3: | ||
* [[Reinforcement Learning (RL)]] | * [[Reinforcement Learning (RL)]] | ||
* [[Deep Reinforcement Learning (DRL)]] | * [[Deep Reinforcement Learning (DRL)]] | ||
| − | * [[Natural Language Processing (NLP | + | * [[Natural Language Processing (NLP)]] |
* [http://medium.com/huggingface/state-of-the-art-neural-coreference-resolution-for-chatbots-3302365dcf30 State-of-the-art neural coreference resolution for chatbots] | * [http://medium.com/huggingface/state-of-the-art-neural-coreference-resolution-for-chatbots-3302365dcf30 State-of-the-art neural coreference resolution for chatbots] | ||
* [http://huggingface.co/coref/ Try the demo - type in your sentence] | * [http://huggingface.co/coref/ Try the demo - type in your sentence] | ||
Revision as of 07:53, 5 January 2019
- Reinforcement Learning (RL)
- Deep Reinforcement Learning (DRL)
- Natural Language Processing (NLP)
- State-of-the-art neural coreference resolution for chatbots
- Try the demo - type in your sentence
- Deterministic Coreference Resolution Demo | Algorithmia
- State-of-the-art neural coreference resolution for chatbots | Thomas Wolf
Coreference is the fact that two or more expressions in a text – like pronouns or nouns – link to the same person or thing. It is a classical Natural language processing task, that has seen a revival of interest in the past two years as several research groups applied cutting-edge deep-learning and reinforcement-learning techniques to it. It is also one of the key building blocks to building conversational Artificial intelligences.
