| ## QA4PC Dataset (paper: Cross-Policy Compliance Detection via Question Answering) | |
| ### Train Sets | |
| To create training set or entailment and QA tasks, download and convert the ShARC data using the following commands: | |
| ``` | |
| wget https://sharc-data.github.io/data/sharc1-official.zip | |
| unzip sharc1-official.zip | |
| python create_train_from_sharc.py -sharc_dev_path sharc1-official/json/sharc_dev.json -sharc_train_path sharc1-official/json/sharc_train.json | |
| ``` | |
| ### Evaluation Sets | |
| #### Entailment Data | |
| The following files contain the data for the entailment task. This includes the policy + questions, a scenario and an answer (_Yes, No, Maybe_). Each datapoint also contain the information from the ShARC dataset such as tree_id and source_url. | |
| - __dev_entailment_qa4pc.json__ | |
| - __test_entailment_qa4pc.json__ | |
| #### QA Data | |
| The following files contain the data for the QA task. | |
| - __dev_sc_qa4pc.json__ | |
| - __test_sc_qa4pc.json__ | |
| The following file contains the expression tree data for the dev and test sets. Each tree includes a policy, a set of questions and a logical expression. | |
| - __trees_dev_test_qa4pc.json__ | |