Difference between revisions of "Neural Coreference"
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* [[Deep Reinforcement Learning]] | * [[Deep Reinforcement Learning]] | ||
| + | * [[Natural Language Inference (NLI) and Recognizing Textual Entailment (RTE)]] | ||
* [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 03:20, 26 May 2018
- Deep Reinforcement Learning
- Natural Language Inference (NLI) and Recognizing Textual Entailment (RTE)
- State-of-the-art neural coreference resolution for chatbots
- Try the demo - type in your sentence
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.
