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README.md

@@ -1,3 +1,17 @@
+---
+language:
+- en
+license:
+- cc-by-4.0
+multilinguality:
+- monolingual
+pretty_name: Camrest
+size_categories:
+- n<1K
+task_categories:
+- conversational
+---
+
 # Dataset Card for Camrest
 
 - **Repository:** https://www.repository.cam.ac.uk/handle/1810/260970
@@ -5,6 +19,16 @@
 - **Leaderboard:** None
 - **Who transforms the dataset:** Qi Zhu(zhuq96 at gmail dot com)
 
+To use this dataset, you need to install [ConvLab-3](https://github.com/ConvLab/ConvLab-3) platform first. Then you can load the dataset via:
+```
+from convlab.util import load_dataset, load_ontology, load_database
+
+dataset = load_dataset('camrest')
+ontology = load_ontology('camrest')
+database = load_database('camrest')
+```
+For more usage please refer to [here](https://github.com/ConvLab/ConvLab-3/tree/master/data/unified_datasets).
+
 ### Dataset Summary
 
 Cambridge restaurant dialogue domain dataset collected for developing neural network based dialogue systems. The two papers published based on this dataset are: 1. A Network-based End-to-End Trainable Task-oriented Dialogue System 2. Conditional Generation and Snapshot Learning in Neural Dialogue Systems. The dataset was collected based on the Wizard of Oz experiment on Amazon MTurk. Each dialogue contains a goal label and several exchanges between a customer and the system. Each user turn was labelled by a set of slot-value pairs representing a coarse representation of dialogue state (`slu` field). There are in total 676 dialogue, in which most of the dialogues are finished but some of dialogues were not.