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First commit with SpaRTUN and StepGame datasets

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+ *.json filter=lfs diff=lfs merge=lfs -text
README.md CHANGED
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- ---
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- license: cc-by-sa-4.0
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- ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ ---
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+ license: cc-by-sa-4.0
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+ ---
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+
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+ dataset_info:
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+ features:
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+ - name: context
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+ dtype: string
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+ - name: question
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+ dtype: string
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+ - name: targets
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+ sequence: string
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+ - name: target_choices
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+ sequence: string
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+ - name: target_scores
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+ sequence: int32
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+ - name: reasoning
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+ dtype: string
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+ - name: source_data
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+ dtype: string
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+ - name: context_id
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+ dtype: int32
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+ - name: question_id
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+ dtype: int32
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+ - name: symbolic_context
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+ dtype: string
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+ - name: symbolic_entity_map
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+ dtype: string
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+ - name: symbolic_question
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+ sequence: string
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+ - name: num_context_entities
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+ dtype: int32
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+ - name: num_question_entities
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+ dtype: int32
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+ - name: question_type
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+ dtype: string
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+ - name: reasoning_types
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+ sequence: string
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+ - name: spatial_types
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+ sequence: string
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+ - name: commonsense_question
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+ dtype: string
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+ - name: canary
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+ dtype: string
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+ - name: comments
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+ sequence: string
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+
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+ configs:
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+ - config_name: "SpaRP-PS1 (SpaRTUN)"
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+ version: 0.1.0
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+ default: true
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+ data_files:
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+ - split: train
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+ path: "SpaRP-PS1 (SpaRTUN)/train.json"
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+ - split: validation
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+ path: "SpaRP-PS1 (SpaRTUN)/val.json"
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+ - split: test
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+ path: "SpaRP-PS1 (SpaRTUN)/test.json"
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+
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+ - config_name: "SpaRP-PS2 (StepGame)"
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+ version: 0.1.0
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+ data_files:
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+ - split: train
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+ path: "SpaRP (StepGame)/PS2/train.json"
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+ - split: validation
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+ path: "SpaRP (StepGame)/PS2/val.json"
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+ - split: test
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+ path: "SpaRP (StepGame)/PS2/test.json"
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+ ---
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+
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+ # Dataset Card for Spatial Reasoning Path (SpaRP)
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+
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+ ## Table of Contents
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+ - [Table of Contents](#table-of-contents)
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+ - [Dataset Description](#dataset-description)
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+ - [Dataset Summary](#dataset-summary)
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+ - [Languages](#languages)
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+ - [Additional Information](#additional-information)
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+ - [Dataset Curators](#dataset-curators)
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+ - [Licensing Information](#licensing-information)
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+ - [Citation Information](#citation-information)
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+
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+
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+ ## Dataset Description
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+
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+ - **Repository: https://github.com/UKPLab/acl2024-sparc-and-sparp**
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+ - **Paper: https://arxiv.org/abs/**
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+ - **Point of Contact: Md Imbesat Hassan Rizvi (http://www.ukp.tu-darmstadt.de/)**
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+
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+ ### Dataset Summary
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+
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+ This dataset is a consolidation of SpaRTUN and StepGame datasets with an extension of additional spatial characterization and reasoning path generation. The methodology is explained in our ACL 2024 paper - [SpaRC and SpaRP: Spatial Reasoning Characterization and Path Generation for Understanding Spatial Reasoning Capability of Large Language Models]().
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+
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+ ### Languages
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+
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+ English
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+
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+ ## Additional Information
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+
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+ You can download the data via:
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+
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+ ```
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+ from datasets import load_dataset
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+
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+ dataset = load_dataset("UKPLab/sparp") # default config is "SpaRP-PS1 (SpaRTUN)"
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+ dataset = load_dataset("UKPLab/TexPrax", "SpaRP-PS2 (StepGame)") # use the "SpaRP-PS2 (StepGame)" tag for the StepGame dataset
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+ ```
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+ Please find more information about the code and how the data was collected on [GitHub](https://github.com/UKPLab/acl2024-sparc-and-sparp).
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+
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+ ### Dataset Curators
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+
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+ Curation is managed by our [data manager](https://www.informatik.tu-darmstadt.de/ukp/research_ukp/ukp_research_data_and_software/ukp_data_and_software.en.jsp) at UKP.
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+
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+ ### Licensing Information
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+
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+ [CC-by-SA 4.0](https://creativecommons.org/licenses/by-sa/4.0/)
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+
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+ ### Citation Information
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+
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+ Please cite this data using:
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+
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+ ```
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+ @inproceedings{rizvi-2024-sparc,
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+ title={SpaRC and SpaRP: Spatial Reasoning Characterization and Path Generation for Understanding Spatial Reasoning Capability of Large Language Models},
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+ author={Rizvi, Md Imbesat Hassan Rizvi and Zhu, Xiaodan and Gurevych, Iryna},
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+ editor = "",
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+ booktitle = "Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics",
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+ month = aug,
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+ year = "2024",
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+ address = "Bangkok, Thailand",
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+ publisher = "Association for Computational Linguistics",
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+ url = "",
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+ doi = "",
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+ pages = "",
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+ }
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+ ```
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