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的单词（和多单词表达）的含义；它是一种人类可读和机器可读的“超级词典”。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境，并完成参与情境的人和事物的角色。例如，单词hire会让人联想到Employment的情况，包括雇主、雇员、职位等的角色；单词vengeance和短语get back at都能唤起人们对复仇的兴趣，它们的角色分别是复仇者（Avenger）、受害方（Injured party）、伤害（Injury）、罪犯（Offender）和惩罚（Punishment）。这些情况被称为语义框架，该项目以框架语义理论为指导，该理论是由加州大学伯克利分校已故教授Charles J. Fillmore提出的。FrameNet词汇数据库目前包括超过1000个语义框架的描述，超过13000个单词和表达的意思（称为词汇单位），以及超过20万个手动注释的例子，这些例子显示了句子的不同部分如何表达不同的角色。框架数据库在自然语言处理中应用广泛；它帮助工程师创建软件，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。成千上万的研究人员和公司已经在使用这种软件进行应用，比如自动分析来自战斗或自然灾害情况的报告，理解财经新闻报道，识别博客和产品网站上的观点表达，以及搜索临床记录和医学研究报告。虽然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框架数据库。多语言框架项目将在语义框架和词汇单位的层面上为不同语言的数据库进行对齐。对齐后的数据库将有助于提高外语教学、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都可以通过添加英语框架网来参与该项目，为其众多用户创建一个更完整、更有用的框架网。

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.