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niltheory/ExistenceTypes

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Hugging Face2023-12-15 更新2024-03-04 收录
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资源简介:
--- task_categories: - text-classification - question-answering - text-generation language: - en pretty_name: occybyte size_categories: - n<1K license: cc-by-sa-4.0 tags: - complex reasoning - creative writing - logic puzzle --- # Dataset Card for Dataset Name <!-- Provide a quick summary of the dataset. --> This dataset is still a work in progress; it's pretty small at the moment. ## Dataset Details ### Dataset Description <!-- Provide a longer summary of what this dataset is. --> The ExistenceTypes dataset is a highly-contextual logic puzzle classifier that is intended to help with contextual understanding. The model will have to pay attention to the surrounding text and not just the keywords. The statements themselves are structured like logic puzzles and some examples requires multi-step reasoning. This is to help the model deduce and infer based on given premises. The statements are either true, false or ambigious based on the IP's rules and consistency as well as Godless, Godliving or Mixed Domain. The overall idea is for the model to understand and generate content within' the themeatic and conceptual framework of my IP. - **Curated by:** [niltheory] - **Funded by [optional]:** [More Information Needed] - **Shared by [optional]:** [More Information Needed] - **Language(s) (NLP):** [More Information Needed] - **License:** [More Information Needed] ### Dataset Sources [optional] <!-- Provide the basic links for the dataset. --> - **Repository:** [More Information Needed] - **Paper [optional]:** [More Information Needed] - **Demo [optional]:** [More Information Needed] ## Uses <!-- Address questions around how the dataset is intended to be used. --> ### Direct Use <!-- This section describes suitable use cases for the dataset. --> [More Information Needed] ### Out-of-Scope Use <!-- This section addresses misuse, malicious use, and uses that the dataset will not work well for. --> [More Information Needed] ## Dataset Structure <!-- This section provides a description of the dataset fields, and additional information about the dataset structure such as criteria used to create the splits, relationships between data points, etc. --> [More Information Needed] ## Dataset Creation ### Curation Rationale <!-- Motivation for the creation of this dataset. --> [More Information Needed] ### Source Data <!-- This section describes the source data (e.g. news text and headlines, social media posts, translated sentences, ...). --> #### Data Collection and Processing <!-- This section describes the data collection and processing process such as data selection criteria, filtering and normalization methods, tools and libraries used, etc. --> [More Information Needed] #### Who are the source data producers? <!-- This section describes the people or systems who originally created the data. It should also include self-reported demographic or identity information for the source data creators if this information is available. --> [More Information Needed] ### Annotations [optional] <!-- If the dataset contains annotations which are not part of the initial data collection, use this section to describe them. --> #### Annotation process <!-- This section describes the annotation process such as annotation tools used in the process, the amount of data annotated, annotation guidelines provided to the annotators, interannotator statistics, annotation validation, etc. --> [More Information Needed] #### Who are the annotators? <!-- This section describes the people or systems who created the annotations. --> [More Information Needed] #### Personal and Sensitive Information <!-- State whether the dataset contains data that might be considered personal, sensitive, or private (e.g., data that reveals addresses, uniquely identifiable names or aliases, racial or ethnic origins, sexual orientations, religious beliefs, political opinions, financial or health data, etc.). If efforts were made to anonymize the data, describe the anonymization process. --> [More Information Needed] ## Bias, Risks, and Limitations <!-- This section is meant to convey both technical and sociotechnical limitations. --> [More Information Needed] ### Recommendations <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> Users should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations. ## Citation [optional] <!-- If there is a paper or blog post introducing the dataset, the APA and Bibtex information for that should go in this section. --> **BibTeX:** [More Information Needed] **APA:** [More Information Needed] ## Glossary [optional] <!-- If relevant, include terms and calculations in this section that can help readers understand the dataset or dataset card. --> [More Information Needed] ## More Information [optional] [More Information Needed] ## Dataset Card Authors [optional] [More Information Needed] ## Dataset Card Contact [More Information Needed]
提供机构:
niltheory
原始信息汇总

数据集卡片 for ExistenceTypes

数据集概述

ExistenceTypes 数据集是一个高度上下文的逻辑谜题分类器,旨在帮助模型进行上下文理解。模型需要关注周围的文本而不仅仅是关键词。这些陈述本身结构类似于逻辑谜题,有些例子需要多步骤推理。

数据集详情

数据集描述

ExistenceTypes 数据集旨在帮助模型根据给定的前提进行推断和推断。陈述基于 IP 的规则和一致性,以及无神论、有神论或混合域,要么为真,要么为假,要么为模糊。总体目标是让模型在 IP 的主题和概念框架内理解和生成内容。

  • 由 [niltheory] 策划
  • 语言(s) (NLP): 英语
  • 许可证: cc-by-sa-4.0

数据集标签

  • 任务类别: 文本分类, 问答, 文本生成
  • 语言: 英语
  • 大小类别: n<1K
  • 标签: 复杂推理, 创意写作, 逻辑谜题

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