--- license: cc-by-sa-4.0 dataset_info: features: - name: context dtype: string - name: question dtype: string - name: targets sequence: string - name: target_choices sequence: string - name: target_scores sequence: int32 - name: reasoning dtype: string - name: source_data dtype: string - name: context_id dtype: int32 - name: question_id dtype: int32 - name: symbolic_context dtype: string - name: symbolic_entity_map dtype: string - name: symbolic_question sequence: string - name: symbolic_reasoning dtype: string - name: num_context_entities dtype: int32 - name: num_question_entities dtype: int32 - name: question_type dtype: string - name: reasoning_types sequence: string - name: spatial_types sequence: string - name: commonsense_question dtype: string - name: canary dtype: string - name: comments sequence: string configs: - config_name: "SpaRP-PS1 (SpaRTUN)" version: 1.1.0 data_files: - split: train path: "sparp/SpaRP-PS1 (SpaRTUN)/train.json" - split: validation path: "sparp/SpaRP-PS1 (SpaRTUN)/val.json" - split: test path: "sparp/SpaRP-PS1 (SpaRTUN)/test.json" - config_name: "SpaRP-PS2 (StepGame)" version: 1.1.0 data_files: - split: train path: "sparp/SpaRP (StepGame)/PS2/train.json" - split: validation path: "sparp/SpaRP (StepGame)/PS2/val.json" - split: test path: "sparp/SpaRP (StepGame)/PS2/test.json" - config_name: "SpaRP-PS3 (StepGame-Ext-01)" version: 1.1.0 data_files: - split: train path: "sparp/SpaRP (StepGame)/PS3/train.json" - split: validation path: "sparp/SpaRP (StepGame)/PS3/val.json" - split: test path: "sparp/SpaRP (StepGame)/PS3/test.json" - config_name: "SpaRP-PS4 (StepGame-Ext-02)" version: 1.1.0 data_files: - split: train path: "sparp/SpaRP (StepGame)/PS4/train.json" - split: validation path: "sparp/SpaRP (StepGame)/PS4/val.json" - split: test path: "sparp/SpaRP (StepGame)/PS4/test.json" - config_name: "small-SpaRP-PS1 (SpaRTUN)" version: 1.1.0 data_files: - split: train path: "small-sparp/SpaRP-PS1 (SpaRTUN)/train.json" - split: validation path: "small-sparp/SpaRP-PS1 (SpaRTUN)/val.json" - split: test path: "small-sparp/SpaRP-PS1 (SpaRTUN)/test.json" - config_name: "small-SpaRP-PS2 (StepGame)" version: 1.1.0 data_files: - split: train path: "small-sparp/SpaRP (StepGame)/PS2/train.json" - split: validation path: "small-sparp/SpaRP (StepGame)/PS2/val.json" - split: test path: "small-sparp/SpaRP (StepGame)/PS2/test.json" - config_name: "small-SpaRP-PS3 (StepGame-Ext-01)" version: 1.1.0 data_files: - split: train path: "small-sparp/SpaRP (StepGame)/PS3/train.json" - split: validation path: "small-sparp/SpaRP (StepGame)/PS3/val.json" - split: test path: "small-sparp/SpaRP (StepGame)/PS3/test.json" - config_name: "small-SpaRP-PS4 (StepGame-Ext-02)" version: 1.1.0 data_files: - split: train path: "small-sparp/SpaRP (StepGame)/PS4/train.json" - split: validation path: "small-sparp/SpaRP (StepGame)/PS4/val.json" - split: test path: "small-sparp/SpaRP (StepGame)/PS4/test.json" # - config_name: SpartQA_Human # version: 1.1.0 # data_files: # - split: train # path: "SpartQA_Human/train.json" # - split: validation # path: "SpartQA_Human/val.json" # - split: test # path: "SpartQA_Human/test.json" # - config_name: ReSQ # version: 1.1.0 # data_files: # - split: train # path: "ReSQ/train.json" # - split: validation # path: "ReSQ/val.json" # - split: test # path: "ReSQ/test.json" --- # Dataset Card for Spatial Reasoning Path (SpaRP) ## Table of Contents - [Table of Contents](#table-of-contents) - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Languages](#languages) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) ## Dataset Description - **Repository: https://github.com/UKPLab/acl2024-sparc-and-sparp** - **Paper: https://arxiv.org/abs/** - **Point of Contact: Md Imbesat Hassan Rizvi (http://www.ukp.tu-darmstadt.de/)** ### Dataset Summary 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](). The dataset format and fields are normalized across the two upstream benchmark datasets -- SpaRTUN and StepGame. The datasets are primarily a Spatial Question Answering datasets, which are enriched with verbalized reasoning paths. The prominent fields of interests are: - *context*: Textual description of the spatial context. - *question*: A question about finding spatial relations between two entities in the context. - *targets*: Answer i.e. list of spatial relations between the entities in the question. - *target_choices*: List of all the spatial relations to choose from. - *target_scores*: Binarized Multi-label representation of targets over target_choices. - *reasoning*: Verbalized reasoning path as deductively-verified CoT for training or few-shot examples. Additionally, the fields with the metadata are: - *context_id*: An identifier from the source data corresponding to the context. `context_id` is unique. A single context can have multiple questions (e.g. SpaRTUN). Hence, (context_id, question_id) is a unique identifier for a dataset instance. - *question_id*: An identifier from the source data corresponding to the question. - *num_hop*: Ground truth number of hop required for the question. - *symbolic_context*: A json string describing the symbolic context. - *symbolic_entity_map*: A json string that maps symbolic entities to their complete descriptive names used. - *symbolic_question*: A list containing head and tail entities of the question. - *symbolic_reasoning*: A json string containing symbolic reasoning steps. - *num_context_entities*: Number of entities in the context. - *num_question_entities*: Number of entities in the question. - *question_type*: Type of the question. Only `FR` i.e. Find Relation type questions are currently present. - *canary*: A canary string present only in the `test`. - *reasoning_types*: The type of reasoning copied from the source data required for answering the question. - *spatial_types*: The type of spatial relations copied from the source data required for answering the question. - *source_data*: The upstream source of the data (either SpaRTUN or StepGame) for a given instance. - *comments*: Additional comments specific to the upstream data. ### Languages English ## Additional Information You can download the data via: ``` from datasets import load_dataset dataset = load_dataset("UKPLab/sparp") # default config is "SpaRP-PS1 (SpaRTUN)" dataset = load_dataset("UKPLab/sparp", "SpaRP-PS2 (StepGame)") # use the "SpaRP-PS2 (StepGame)" tag for the StepGame dataset ``` Please find more information about the code and how the data was collected on [GitHub](https://github.com/UKPLab/acl2024-sparc-and-sparp). ### Dataset Curators Curation is managed by our [data manager](https://tudatalib.ulb.tu-darmstadt.de/handle/tudatalib/4235) at UKP. ### Licensing Information [CC-by-SA 4.0](https://creativecommons.org/licenses/by-sa/4.0/) ### Citation Information Please cite this data using: ``` @inproceedings{rizvi-2024-sparc, title={SpaRC and SpaRP: Spatial Reasoning Characterization and Path Generation for Understanding Spatial Reasoning Capability of Large Language Models}, author={Rizvi, Md Imbesat Hassan Rizvi and Zhu, Xiaodan and Gurevych, Iryna}, editor = "", booktitle = "Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics", month = aug, year = "2024", address = "Bangkok, Thailand", publisher = "Association for Computational Linguistics", url = "", doi = "", pages = "", } ```