Abstract
This paper introduces a new, graph-based view of the data of the FrameNet project, which we hope will make it easier to understand the mixture of semantic and syntactic information contained in FrameNet annotation. We show how English FrameNet and other Frame Semantic resources can be represented as sets of interconnected graphs of frames, frame elements, semantic types, and annotated instances of them in text. We display examples of the new graphical representation based on the annotations, which combine Frame Semantics and Construction Grammar, thus capturing most of the syntax and semantics of each sentence. We consider how graph theory could help researchers to make better use of FrameNet data for tasks such as automatic Frame Semantic role labeling, paraphrasing, and translation. Finally, we describe the development of FrameNet-like lexical resources for other languages in the current Multilingual FrameNet project. which seeks to discover cross-lingual alignments, both in the lexicon (for frames and lexical units within frames) and across parallel or comparable texts. We conclude with an example showing graphically the semantic and syntactic similarities and differences between parallel sentences in English and Japanese. We will release software for displaying such graphs from the current data releases.
Highlights
In this paper, we provide a new graph-based display of FrameNet annotation, which we hope will make the complex data model of FrameNet more accessible to a variety of users
The FrameNet Project [Fillmore and Baker, 2010, Ruppenhofer et al, 2016] at the International Computer Science Institute (ICSI) is an ongoing project to produce a lexicon of English that is both human- and machine-readable, based on the theory of Frame Semantics developed by Charles Fillmore and colleagues [Fillmore, 1997] and supported by annotating corpus examples of the lexical items
FrameNet (FN) is a lexical resource, it is organized not around words, but rather the roughly 1,200 semantic frames [Fillmore, 1976]: characterizations of events, relations, states and entities which are the conceptual basis for understanding the word senses, called lexical units (LUs)
Summary
We provide a new graph-based display of FrameNet annotation, which we hope will make the complex data model of FrameNet more accessible to a variety of users. We begin with a brief introduction to the Frame Semantics and the FrameNet project and their underlying graph structures. 4 discusses how the graph representation could help NLP developers, w.r.t. automatic semantic role labeling. 5, we introduce the Multilingual FrameNet project, and what comparisons of frame structures across languages might reveal by way of another example sentence in the new format, discuss our conclusions and acknowledge support for our work
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