CI-ADDO-EN: FrameNet 3: Upgrading FrameNet for the NLP Community

CI-ADDO-EN：FrameNet 3：为 NLP 社区升级 FrameNet

• 批准号: 0855271
• 负责人: Collin Baker
• 金额: --
• 依托单位: International Computer Science Institute
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-08-01 至 2011-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0855271&HistoricalAwards=false
• 关键词: CI; ADDO; EN; FrameNet; Upgrading

The FrameNet project has been building a lexical database containinghighly detailed information about the syntax and semantics of thedifferent senses of English words, with applications such as questionanswering and information extraction. The database is based onCharles Fillmore's theory of Frame Semantics, relating word meaningsto conceptualizations of situations and their participants, rangingfrom simple actions like Placing to complex events such as a Criminalprocess, with subevents like Arraignment and Trial. Thegeneralizations are derived from annotated example sentences fromlarge text corpora.In this planning grant, input will be gathered from researchers in theNLP field regarding how the FrameNet data is currently being used, howit can be made more useful to a wider range of users, and how it canbe enhanced so as to enable new directions of research. As part ofthis, a series of conferences will be held, both face-to-face and byvideoconference, to plan future FrameNet development and cooperationand alignment of data with other lexical resources and annotationprojects, such as WordNet, PropBank, OntoNotes, etc., with theultimate goal of improving results in sense disambiguation, semanticrole recognition, and natural language understanding in general.

框架网项目一直在建立一个词汇数据库，其中包含关于英语单词不同意义的语法和语义的非常详细的信息，并应用于问答和信息提取等应用。该数据库基于查尔斯·菲尔莫尔的框架语义学理论，将单词的含义与情境及其参与者的概念化联系起来，从简单的动作（如放置）到复杂的事件（如刑事过程），再到子事件（如提审和审判）。这些概括来自于大型文本语料库中带注释的例句。在这项计划拨款中，将从theNLP领域的研究人员那里收集有关目前如何使用框架网数据的意见，如何使其对更广泛的用户更有用，以及如何加强它以实现新的研究方向。作为其中的一部分，将举行一系列面对面和视频会议，以规划未来框架的发展以及与其他词汇资源和注释项目（如WordNet、PropBank、OntoNotes等）的数据合作和对齐，最终目标是提高意义消歧、语义角色识别和自然语言理解的结果。