CI-P: Collaborative Research: LexLink: Aligning WordNet, FrameNet, PropBank and VerbNet

CI-P：协作研究：LexLink：对齐 WordNet、FrameNet、PropBank 和 VerbNet

• 批准号: 1205473
• 负责人: Christiane Fellbaum
• 金额: $ 4.5万
• 依托单位: Princeton University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-06-01 至 2013-05-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1205473&HistoricalAwards=false
• 关键词: CI; Collaborative; Research; LexLink; Aligning

This Computing Research Infrastructure planning grant addresses two challenges for automatic systems performing deep semantic processing: identifying the context-appropriate sense of polysemous words and interpreting the meanings and interrelations of verbs and nouns in event-denoting phrases. Preliminary steps are taken for aligning and linking four existing widely used lexical resources (WordNet, FrameNet, PropBank and VerbNet) with different but complementary contents and coverage. Methods for completing current cross-resource links and full transitive closure are explored and tested. The resulting infrastructure (LexLink) is designed to make the resources fully interoperable, capitalizing on their particular strengths with respect to word sense disambiguation and Semantic Role labeling.Four activities are carried out in the context of planning LexLink. First, a workshop is held where key representatives of the Natural Language Processing and computational semantics communities articulate needs and requirements for the planned resource and offer advice on algorithms, annotation techniques and evaluation. Second, a subsection of cross-resource links for word senses and Semantic Role labels (Agent, Instrument, etc.) resulting from the automatic transitive closure is evaluated, yielding estimates for the error rate and leading to fine-tuning of algorithms. Third, current best performing mapping algorithms for word senses and Semantic Role labels are evaluated against a human-annotated Gold Standard. Fourth, new Gold Standard data are created for additional training and testing and to refine existing algorithms. As a whole, the work provides a solid foundation for a resource with significant beneficial impact on a range of natural language applications, including machine translation, text summarization and sentiment analysis affecting areas such as health care, marketing, and education.

这项计算研究基础架构计划赠款解决了执行深度语义处理的自动系统的两个挑战：确定具有上下文的多义单词的适当意义，并解释了段落段落短语中动词和名词的含义和相互关系。初步步骤是为了对齐和链接四个现有的广泛使用的词汇资源（WordNet，Framenet，Propbank和Verbnet），并具有不同但互补的内容和覆盖范围。探索并测试了完成当前跨资源链接和完全及时闭合的方法。由此产生的基础架构（Lexlink）旨在使资源完全可互操作，并利用其在单词Sense dismandigation和语义角色标签方面的特殊优势。在规划Lexlink的背景下，进行了四项活动。首先，举行了一个研讨会，其中自然语言处理和计算语义社区的主要代表表达了计划中的资源的需求和要求，并提供有关算法，注释技术和评估的建议。其次，评估了由自动及其换闭闭合产生的单词感官和语义角色标签（代理，仪器等）的跨资源链接的小节，从而得出了错误率的估计，并导致算法的微调。第三，针对人类宣布的金标准评估了当前的最佳性能映射算法和语义角色标签。第四，创建了新的黄金标准数据，用于额外的培训和测试并完善现有算法。总体而言，这项工作为对一系列自然语言应用具有重大有益影响的资源奠定了坚实的基础，包括机器翻译，文本摘要和影响诸如医疗保健，营销和教育等领域的情感分析。