| # 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) |
|
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| Find more about us at [mango.ttic.edu](https://mango.ttic.edu) |
|
|
| ## Folder Structure |
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| 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 |
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| 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. |
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| * **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. |
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| * **All-step** `data.tar.zst`: contains all steps of each walkthrough. |
|
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| ### Word-only & Word+ID |
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| * **Word-only** `data.tar.zst`: Nodes are annotated by additional descriptive text to distinguish different locations with similar names. |
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| * **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. |
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| * **Word + Random ID** `data-randid.tar.zst`: variation of the Jericho ID version, where the Jericho object id replaced with randomly generated integer. |
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| We primarily rely on the **word-only** version as benchmark, yet providing word+ID version for diverse benchmark settings. |
|
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| ## How to use |
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| We use `data.tar.zst` as an example here. |
|
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| ### 1. download from Huggingface |
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| #### by directly download |
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| You can selectively download certain variation of your choice. |
|  |
|
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| #### by git |
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| 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 |
| ``` |
|
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| If you want to clone without large files - just their pointers |
|
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| ```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 |
| ``` |
|
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| ### 2. decompress |
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| Because some json files are huge, we use tar.zst to package the data efficiently. |
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| silently decompress |
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| ```bash |
| tar -I 'zstd -d' -xf data.tar.zst |
| ``` |
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| or, verbosely decompress |
|
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| ```bash |
| zstd -d -c data.tar.zst | tar -xvf - |
| ``` |
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|
