| # data | |
| If you are looking for our intermediate labeling version, please refer to [mango-ttic/data-intermediate](https://huggingface.co/datasets/mango-ttic/data-intermediate) | |
| Find more about us at [mango.ttic.edu](https://mango.ttic.edu) | |
| ## Folder Structure | |
| Each folder inside `data` contains the cleaned up files used during LLM inference and results evaluations. Here is the tree structure from game `data/night` . | |
| ```bash | |
| data/night/ | |
| ├── night.actions.json # list of mentioned actions | |
| ├── night.all2all.jsonl # all simple paths between any 2 locations | |
| ├── night.all_pairs.jsonl # all connectivity between any 2 locations | |
| ├── night.edges.json # list of all edges | |
| ├── night.locations.json # list of all locations | |
| └── night.walkthrough # enriched walkthrough exported from Jericho simulator | |
| ``` | |
| ## Variations | |
| ### 70-step vs all-step version | |
| In our paper, we benchmark using the first 70 steps of the walkthrough from each game. We also provide all-step versions of both `data` and `data-intermediate` collection. | |
| * **70-step** `data-70steps.tar.zst`: contains the first 70 steps of each walkthrough. If the complete walkthrough is shorter than 70 steps, then all steps are used. | |
| * **All-step** `data.tar.zst`: contains all steps of each walkthrough. | |
| ### Word-only & Word+ID | |
| * **Word-only** `data.tar.zst`: Nodes are annotated by additional descriptive text to distinguish different locations with similar names. | |
| * **Word + Object ID** `data-objid.tar.zst`: variation of the word-only version, where nodes are labeled using minimaly fixed names with object id from Jericho simulator. | |
| * **Word + Random ID** `data-randid.tar.zst`: variation of the Jericho ID version, where the Jericho object id replaced with randomly generated integer. | |
| We primarily rely on the **word-only** version as benchmark, yet providing word+ID version for diverse benchmark settings. | |
| ## How to use | |
| We use `data.tar.zst` as an example here. | |
| ### 1. download from Huggingface | |
| #### by directly download | |
| You can selectively download certain variation of your choice. | |
|  | |
| #### by git | |
| Make sure you have [git-lfs](https://git-lfs.com) installed | |
| ```bash | |
| git lfs install | |
| git clone https://huggingface.co/datasets/mango-ttic/data | |
| # or, use hf-mirror if your connection to huggingface.co is slow | |
| # git clone https://hf-mirror.com/datasets/mango-ttic/data | |
| ``` | |
| If you want to clone without large files - just their pointers | |
| ```bash | |
| GIT_LFS_SKIP_SMUDGE=1 git clone https://huggingface.co/datasets/mango-ttic/data | |
| # or, use hf-mirror if your connection to huggingface.co is slow | |
| # GIT_LFS_SKIP_SMUDGE=1 git clone https://hf-mirror.com/datasets/mango-ttic/data | |
| ``` | |
| ### 2. decompress | |
| Because some json files are huge, we use tar.zst to package the data efficiently. | |
| silently decompress | |
| ```bash | |
| tar -I 'zstd -d' -xf data.tar.zst | |
| ``` | |
| or, verbosely decompress | |
| ```bash | |
| zstd -d -c data.tar.zst | tar -xvf - | |
| ``` | |