| # Neural Belief Tracker | |
| Contact: Nikola Mrkšić ([email protected]) | |
| An implementation of the Fully Data-Driven version of the Neural Belief Tracking (NBT) model (ACL 2018, [Fully Statistical Neural Belief Tracking](https://arxiv.org/abs/1805.11350)). | |
| This version of the model uses a learned belief state update in place of the rule-based mechanism used in the original paper. Requests are not a focus of this paper and should be ignored in the output. | |
| ### Configuring the Tool | |
| The config file in the config directory specifies the model hyperparameters, training details, dataset, ontologies, etc. | |
| ### Running Experiments | |
| train.sh and test.sh can be used to train and test the model (using the default config file). | |
| track.sh uses the trained models to 'simulate' a conversation where the developer can enter sequential user turns and observe the change in belief state. | |