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Nature language understanding (NLU) is a subtopic of natural-language processing in artificial intelligence that deals with machine reading comprehension. Natural-language understanding is considered an AI-hard problem. NLU tasks including two main components: Intent Classification (IC) and Named Entities Recognition (NER).
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arizona nluprovide a library for jointly IC and NER tasks based on Transformers architecture.
| text | intent | tags |
|---|---|---|
| hello you, i need a coffe | demand | O O O O O B-food |
[1]. Qian Chen, Zhu Zhuo and Wen Wang: “BERT for Joint Intent Classification and Slot Filling”, in arXiv:1902.10909, 2019.
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arizona.nlu was developed by Phuc Phan © Copyright 2021.
For any questions or comments, please contact the following email: phanxuanphucnd@gmail.com
Our code is based on the unofficial implementation of the JointBERT+CRF github and paper.