WordNet as an Interlingual Lexical Resource

WordNet 作为语际词汇资源

• 批准号: 9805732
• 负责人: Christiane Fellbaum
• 金额: $ 9.98万
• 依托单位: Princeton University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 1998
• 资助国家: 美国
• 起止时间: 1998-11-15 至 2000-10-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9805732&HistoricalAwards=false
• 关键词: WordNet; Interlingual; Lexical; Resource

This work represents a two-pronged extension of the lexical database WordNet to create a resource suitable for automated word sense disambiguation, multilingual adoption, and crosslinguistic applications. Mapping WordNet's words and concepts into those of other languages requires disambiguation, identification, and discrimination of related entities. We first group WordNet's finely distinguished senses of highly polysemous nouns, verbs, and adjectives into underspecified "super"-senses to facilitate discrimination and disambiguation. Second, we add to the verbs in WordNet sentences illustrating their subcategorization patterns and selectional restrictions so as to better distinguish senses and facilitate matching the verb lexicons of different languages. The project is significant because it creates a resource that meets present demands for multilingual Natural Language Processing applications. Moreover, the augmentations carry considerable theoretical interest. Systematic underspecification of lexical entries might lead towards a psychologically realistic lexicon. A principled grouping of closely related senses will shed light on the nature of polysemy and specific ways in which flexible word meanings yield possible sense extensions in all areas of the lexicon. Subcategorization information and selectional restrictions will reveal the extent to which the semantic relatedness of verbs, expressed in WordNet's relational structure, is correlated with syntactic relatedness.

这项工作代表了词汇数据库WordNet的两方面扩展，以创建适合自动词义消歧、多语言采用和跨语言应用的资源。将WordNet的单词和概念映射到其他语言的单词和概念需要消除歧义，识别和区分相关实体。我们首先将WordNet中高度多义的名词、动词和形容词的精细区分的意义归类为未明确的“超级”意义，以便于区分和消除歧义。其次，我们在WordNet句子中添加动词的子分类模式和选择限制说明，以便更好地区分意义，促进不同语言动词词汇的匹配。该项目意义重大，因为它创建了满足多语言自然语言处理应用程序当前需求的资源。此外，这些增广具有相当大的理论意义。系统的词汇不规范可能导致心理现实的词汇。对密切相关的意义进行有原则的分组将揭示多义词的本质，以及灵活的词义在词汇的所有领域产生可能的意义扩展的具体方式。子范畴信息和选择限制将揭示动词在WordNet关系结构中表达的语义关联与句法关联的关联程度。