CRI: CRD A Richly Annotated Resource for Language Processing and Linguistics Research

CRI：CRD 语言处理和语言学研究的注释丰富的资源

• 批准号: 0708952
• 负责人: Nancy Ide
• 金额: $ 93.5万
• 依托单位: Vassar College
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2007
• 资助国家: 美国
• 起止时间: 2007-08-01 至 2014-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0708952&HistoricalAwards=false
• 关键词: CRI; CRD; Richly; Annotated; Resource

This project is annotating a corpus of American English for a variety of linguistic features, including syntactic structures and semantic information. The semantic information includes frame information based on FrameNet together with sense information based on WordNet. The annotations in the corpus are manually assigned by human annotators to ensure their reliability. Bootstrapping methods, using portions of the hand validated annotations, are being used to improve the performance of automatic annotation tools. The corpus is drawn from the materials in the American National Corpus, which consists of written data and speech transcriptions generated y native speakers of American English and representing a broad range of genres. All of the annotations are represented in a common format to enable merging different annotation layers, so that interactions among different linguistic phenomena can be studied.The manually annotated corpus will provide an unparalleled resource for computational linguists and linguists who seek to identify patterns of syntactic and semantic usage that can feed the development of language models. This information can be used to train software to automatically annotate unseen data, which in turn enhances applications such as information retrieval and extraction and machine translation. Usage patterns for American English are also invaluable for the development of materials and tools to support English language learning. The resulting corpus and its annotations, together with tools for manipulating the data, will be made freely available for research purposes through the Linguistic Data Consortium.

本项目是对一个美国英语语料库进行注释，以获得各种语言特征，包括句法结构和语义信息。语义信息包括基于FrameNet的框架信息和基于WordNet的意义信息。 语料库中的注释由人工注释者手动分配，以确保其可靠性。引导方法，使用部分手工验证的注释，正在被用来提高自动注释工具的性能。该语料库是从美国国家语料库中提取的，由美国英语母语者的书面材料和语音翻译组成，代表了广泛的体裁。 所有的注释都以一种通用的格式表示，以便合并不同的注释层，从而可以研究不同语言现象之间的相互作用。人工注释的语料库将为计算语言学家和语言学家提供无与伦比的资源，他们寻求识别句法和语义使用模式，以促进语言模型的发展。这些信息可以用来训练软件自动注释看不见的数据，这反过来又增强了信息检索和提取以及机器翻译等应用。美国英语的使用模式对于开发支持英语学习的材料和工具也是非常宝贵的。由此产生的语料库及其注释，连同操纵数据的工具，将通过语言数据联合会免费提供，用于研究目的。