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

该项目正在对美国英语语料库进行注释，以获得包括句法结构和语义信息在内的各种语言特征。语义信息包括基于FrameNet的框架信息和基于WordNet的语义信息。语料库中的标注是由人工标注人员手动分配的，以确保它们的可靠性。使用部分手工验证的注释的引导方法正被用于提高自动注释工具的性能。语料库来自美国国家语料库，该语料库由以美国英语为母语的人生成的书面数据和语音转录组成，代表了广泛的体裁。人工标注语料库将为计算语言学家和语言学家提供一个无与伦比的资源，他们寻求识别句法和语义使用模式，从而为语言模型的开发提供支持。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程序。美式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。产生的语料库及其注释以及处理数据的工具将通过语言数据联盟免费提供用于研究目的。

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.