The FrameNet model and its applications

The FrameNet database comprises in English lexicon, organized in terms or semantic frames. Frames describe situations or entities, along with their participants and props, termed frame elements. The frames are organized in an ontology-like network. For the lexical units, corpus annotations illustrate which frame elements are typically realized, and how they behave syntactically. Texts where all content words are annotated with FrameNet information offer a detailed, structured semantic representation with a variety of uses in Natural Language Processing applications, in particular in retrieving and meaningfully organizing texts written by humans, or in making human computer interaction more natural. Also, the FrameNet English lexicon can be replaced by lexical data from other languages, while maintaining frame information, so the model is attractive for cross-lingual resources and applications. Manual annotation produced by FrameNet and similar projects for other languages is used to train automatic frame semantic annotation systems, which add rich semantic information to any type or text, and are important components for more sophisticated semantic processing applications.