CI-NEW: Multilingual FrameNet: A Resource Enabling Cross-Lingual Research for the Natural Language Processing Community

FrameNet词汇语义数据库记录了日常英语中单词（和多词表达）的含义;它是一种“超级字典”，既可以人类阅读，也可以机器阅读。 这个数据库是基于这样一个事实，即单个单词可以在我们的脑海中唤起整个情况，并完成参与该情况的人和事物的角色。 例如，hire这个词让人联想到雇佣的情况，有雇主、雇员、职位等角色; 复仇这个词和回到唤起复仇，角色复仇者，受伤方，伤害，罪犯和惩罚。 这些情况被称为语义框架，该项目由加州大学伯克利分校已故教授Charles J. Fillmore开发的框架语义学理论指导。 FrameNet词汇数据库目前包括1,000多个语义框架、13,000多个词义和表达的描述（称为词汇单位），以及超过20万个人工注释的例子，这些例子展示了句子的不同部分如何表达各种角色。FrameNet数据库广泛用于自然语言处理;它可以帮助工程师开发软件，将书面文本分析成语义框架和参与者，这样计算机就可以对所描述的情况进行推理。数以千计的研究人员和公司已经在使用这种软件，例如自动分析战斗或自然灾害情况的报告，理解金融新闻报道，识别博客和产品网站上的意见表达，以及搜索临床记录和医学研究报告。虽然这些框架主要是为英语创建的，但它们中的大多数已经被证明对其他语言也很有用，世界各地的研究人员现在正在为许多其他语言创建FrameNet数据库。 多语言框架网项目将在语义框架和词汇单位两个层面上为不同语言调整数据库。 对齐的数据库将有助于改进外语教学、跨语言信息检索和机器翻译等应用。 新项目还包括建立一个网站和软件，以便各地的教师和学生可以通过添加到英语框架网络来参与该项目，为众多用户创建一个更完整、更有用的框架网络。

The FrameNet lexical semantic database records the meanings of words (and multi-word expressions) in everyday English; it is a sort of "super dictionary" that is both human-readable and machine-readable. This database is based on the fact that individual words can evoke and entire situation in our minds, complete with roles for people and things that participate in the situation. For example, the word hire evokes the situation of Employment, with roles for the Employer, the Employee, the Position, etc.; both the word vengeance and the expression get back at evoke Revenge, with the roles Avenger, Injured party, Injury, Offender, and Punishment. These situations are called semantic frames, and the project is guided by the theory of Frame Semantics, developed by the late Prof. Charles J. Fillmore of UC Berkeley. The FrameNet lexical database currently includes descriptions of more than 1,000 semantic frames, more than 13,000 senses of words and expressions (called Lexical units), and more than 200,000 manually annotated examples which show how the various roles are expressed by different parts of a sentence.The FrameNet database is widely used in natural language processing; it helps engineers create software to analyze written texts into semantic frames and participants, so that computers can reason about the situations described. Thousands of researchers and companies are already using such software for applications such as automatic analysis of reports from combat or natural disaster situations, understanding financial news reports, recognizing expressions of opinion on blogs and product websites, and searching clinical records and medical research reports. Although the frames were mainly created for English, most of them have been shown to be useful for other languages as well, and researchers around the world are now creating FrameNet databases for many other languages. The Multilingual FrameNet project will align the databases for different languages, both at the level of semantic frames and at the level of lexical units. The aligned database will help to improve applications such as foreign language teaching, cross-linguistic information retrieval, and machine translation. The new project also includes setting up a website and software so that teachers and students everywhere can participate in the project by adding to English FrameNet, creating a more complete and more useful FrameNet for its many users.