Generating Semantic Graph Corpora with Graph Expansion Grammar
This provides a method for generating synthetic data to augment corpora and serves as a pedagogical tool for teaching formal language theory, but it is incremental as it builds on existing grammar-based approaches.
The authors tackled the problem of creating semantic graph corpora by introducing Lovelace, a tool that uses graph expansion grammar to generate well-formed graphs based on user-defined grammars, enabling control over properties like graph size.
We introduce Lovelace, a tool for creating corpora of semantic graphs. The system uses graph expansion grammar as a representational language, thus allowing users to craft a grammar that describes a corpus with desired properties. When given such grammar as input, the system generates a set of output graphs that are well-formed according to the grammar, i.e., a graph bank. The generation process can be controlled via a number of configurable parameters that allow the user to, for example, specify a range of desired output graph sizes. Central use cases are the creation of synthetic data to augment existing corpora, and as a pedagogical tool for teaching formal language theory.