RI: Collaborative Proposal: Complementary Lexical Resources: Towards an Alignment of WordNet and FrameNet

机器可读的词汇资源对于信息提取和机器翻译等自然语言处理应用至关重要。最大的词典是WordNet，它的语义信息超过150,000个，或者说是词汇单位（lexical units, lu）。一个较小的、独立开发的资源是FrameNet，它提供了关于逻辑单元语法模式的详细信息。该项目调查了这些互补资源的组合方式，在可用的情况下，使用来自框架网（FN）的语义-句法信息，在其他情况下，使用来自WordNet （WN）的不太详细的条目。WN和FN表现出根本不同的设计原则。WN将（近）同义的逻辑单元分组为“同义词集”，这些同义词集通过概念和词汇关系相互连接，形成语义网络。FN根据它们所唤起的“语义框架”对lu进行分组，语义框架是指事件、关系或状态的类型，以及事件中涉及的参与者。因此，虽然像表扬和责备这样的反义词可能在同一个FN框架中，但它们在不同的WN同义词集中，尽管它们是相互联系的。此外，FN框架涵盖了语义相关的名词、动词和形容词；语法集不会混淆词性。对于NLP应用至关重要的是，这些资源在感觉区分方面有所不同。对齐将调查以下差异：词汇覆盖范围，意义区别，分类和其他语义关系，以及形容词的标量框架。我们对大约1000个词义进行了详细的研究，以便对每一种现象在整个词典中的分布情况有一个大致的了解。这项理论工作为构建一个独特的、宝贵的NLP社区资源奠定了基础。

Machine-readable lexical resources are essential to Natural LanguageProcessing applications such as information extraction and machine translation. The largest lexicon is WordNet, with semantic information about more than 150,000, or lexical units (LUs). A smaller, independently developed resource is FrameNet, which provides detailed information about the syntactic patterns for LUs. The project investigates the ways in which these complementary resources can be combined using the semantic-syntactic information fromFrameNet (FN) where available and falling back on less detailedentries from WordNet (WN) in other cases. WN and FN exhibit fundamentally different design principles. WN groups (near) synonymous LUs into "synsets," which are interconnected via conceptual and lexical relations to form a semantic network. FN groups LUs according to the"semantic frame" they evoke, which is a type of event, relation orstate along with the participants involved in the event. Thus,while antonyms such as _praise_ and _blame_ may be in the same FN frame they are in different, though interlinked, WN synsets. Moreover, FN frames cover semantically related nouns, verbs and adjectives; WN synsetsdo not mix part of speech. Crucially for NLP applications, the resources differ with respect to sense distinctions.Alignment will be investigated for the following differences: lexical coverage, sense distinctions, taxonomic andother semantic relations, and scalar frames for adjectives.Some 1,000 word senses are examined in detail so as to provide an idea ofthe distribution of each of these phenomena over the entire lexicon. This theoretical work lays the foundation for constructing a unique, invaluable resource for the NLP community.