INTEROP: Lexicon Enhancement via the GOLD Ontology (LEGO)

该项目将为语言学和使用语言数据的所有学科的数据互操作性提供几个“积木”。这项工作将基于语言描述的通用本体（GOLD），这是一种机器可读的信息结构，允许计算机处理和“理解”语言概念及其之间的关系。使用GOLD，该项目将开发一个广泛的本体感知词汇项网络，这些词汇项来自16个不同的项目和3000多种语言。因此，计算机将能够理解不同语言之间的语言类别之间的关系，并解释它们在文本中出现时的语言功能。此外，该项目将开发一套低障碍的数据要求，词典创建者可以实现，以加入这个基于本体的网络。它还将创建架构，将网络数据纳入主要国际标准倡议制定的框架。最后，该项目将建立DevSpace，这是一个在线设施，旨在促进有兴趣用其他工具和服务扩大网络的语言学家和开发人员之间持续的信息和资源共享，这样一个项目很重要，因为跨语言的语言数据是许多研究团体的核心。语言历史和语言比较可以为人类的遗传、文化、迁移和接触提供重要的见解。自然语言数据对于主要的计算研究计划是不可或缺的，例如多语言文本处理。通过从如此多的未被描述的语言中提供语言解释的词汇数据，乐高最终将帮助从文本中提取含义，即使是太小的语言，也无法证明全面的自然语言处理系统的合理性。因此，从计算的角度和人文社会科学的角度来看，乐高项目将创建一个研究资源的显着广度和多样性，这将服务于多个学科。

This project will furnish several 'building blocks' for data interoperability within linguistics and all disciplines which use language data. The work will be based on the General Ontology for Linguistic Description (GOLD), a machine-readable information structure which allows allows computers to process and 'understand' linguistic concepts and the relations among them. Using GOLD, the project will develop an extensive network of ontology-aware lexical items drawn from sixteen different projects and over 3000 languages. Thus, computers will be able to understand the relationship between linguistic categories across languages, and interpret what their linguistic function is when they appear in texts. In addition, the project will develop a set of low-barrier data requirements which lexicon creators can implement in order to join this ontology-based network. It will also create architecture to integrate network data into frameworks developed by major international standards initiatives. Finally, the project will establish DevSpace, an online facility designed to promote continuing information- and resource-sharing among linguists and developers interested in augmenting the network with additional tools and services.Such a project is important because cross-linguistic language data is central to many research communities. Language history and language comparison can provide critical insights into the genetics, culture, migrations, and contacts of human populations. And natural language data is indispensable to major computational research initiatives, such as multilingual text processing. In providing linguistically interpreted lexical data from so many underdescribed languages, LEGO will ultimately aid in meaning extraction from texts even of languages far too small to justify a full-scale natural language processing system. Thus from both a computational perspective and a Humanities and Social Sciences perspective, the LEGO project will create a research resource of remarkable breadth and diversity, one which will serve multiple disciplines.