The field of Natural Language Processing (NLP) is growing rapidly, with new research published daily along with an abundance of tutorials, codebases and other online resources. In order to learn this dynamic field or stay up-to-date on the latest research, students as well as educators and researchers must constantly sift through multiple sources to find valuable, relevant information. To address this situation, we introduce TutorialBank, a new, publicly available dataset which aims to facilitate NLP education and research. We have manually collected and categorized over 6,300 resources on NLP as well as the related fields of Artificial Intelligence (AI), Machine Learning (ML) and Information Retrieval (IR). Our dataset is notably the largest manually-picked corpus of resources intended for NLP education which does not include only academic papers. Additionally, we have created both a search engine and a command-line tool for the resources and have annotated the corpus to include lists of research topics, relevant resources for each topic, prerequisite relations among topics, relevant sub-parts of individual resources, among other annotations. We are releasing the dataset and present several avenues for further research.

TutorialBank是一个新的、公开可用的数据集，旨在促进NLP教育和研究。该数据集手动收集和分类了超过6300个NLP以及相关领域的资源，是目前最大的人工选取的旨在用于NLP教育的资源语料库之一，而且还创建了搜索引擎和命令行工具，为这些资源进行了注释。

TutorialBank：一个人工收集的语料库，用于先决条件链、调查提取和资源推荐