FrameNet Workshop: Developing New NLP Applications

近年来，设计用于理解普通语言的计算机系统已经迅速改进。 这些进步部分取决于改善语言资源，帮助系统识别单个单词的不同含义以及句子的各个部分如何组合在一起。 人们主要通过将单词与常见的情景联系起来来理解它们;在“She throwed the letter across the table to Jerry”中，人们认识到主要思想来自“toss”，并理解“she”，“the letter”，“across the table”和“to Jerry”扮演的不同角色。 在过去的15年里，国际计算机科学研究所的FrameNet团队一直在定义被称为语义框架的情景，并在说明性句子的组成部分上标记具有语义角色的示例。 FrameNet知识数据库包含1,100多个语义框架，从找工作到治疗疾病，以及近20万个标记句子。其他研究人员已经创建了基于FrameNet数据自动标记开放文本中的句子的软件;这些自动语义角色标记（ASRL）系统促进了从新闻故事和军事报告等文档中自动识别事件及其参与者。该奖项资助了为期一周的研讨会，于2013年9月9日至13日，向更广泛的行业和学术参与者介绍FrameNet。 演讲者包括FrameNet团队以及ASRL系统的开发人员和用户。涵盖的主题范围从保护隐私的框架网络的影响，使用框架理解隐喻。 软件开发人员使用NLTK的新FrameNet库进行动手编码会议;其他参与者执行动手框架定义和注释。

In recent years, computer systems designed to understand ordinary language have improved rapidly. These advances depend in part on improving the language resources that help systems recognize different senses of individual words and how the parts of a sentence fit together. People understand words largely by relating them to common situations; in 'She tossed the letter across the table to Jerry', one recognizes that the main idea comes from 'toss', and understands the different roles that 'she', 'the letter', 'across the table', and 'to Jerry' play. For the past fifteen years, the FrameNet team at the International Computer Science Institute has been defining situations, called semantic frames, and labeling examples with semantic roles on the constituents of illustrative sentences. The FrameNet knowledge database contains over 1,100 semantic frames, ranging from getting a job to curing a disease, and almost 200,000 labeled sentences. Other researchers have created software to automatically label sentences in open text based on FrameNet data; these automatic semantic role labeling (ASRL) systems facilitate the automatic recognition of events and their participants in documents ranging from news stories and military reports.This award funds a one-week workshop, September 9-13, 2013, introducing FrameNet to a wider range of industry and academic participants. Speakers include the FrameNet team as well as developers and users of ASRL systems. Topics covered range from implications of FrameNet for protecting privacy to using frames in understanding metaphor. Software developers have a hands-on coding session using the new FrameNet library for NLTK; other participants perform hands-on frame definition and annotation.