We investigate formalisms for capturing the relation between semantic graphs and English strings. Semantic graph corpora have spurred recent interest in graph transduction formalisms, but it is not yet clear whether such formalisms are a good fit for natural language data―in particular, for describing how semantic reentrancies correspond to English pronouns, zero pronouns, reflexives, passives, nominalizations, etc. We introduce a data set that focuses on these problems, we build grammars to capture the graph/string relation in this data, and we evaluate those grammars for conciseness and accuracy.

When training semantic role labeling systems, the syntax of example sentences is of particular importance. Unfortunately, for the FrameNet annotated sentences, there is no standard parsed version. The integration of the automatic parse of an annotated sentence with its semantic annotation, while conceptually straightforward, is complex in practice. We present a standard dataset that is publicly available and that can be used in future research. This dataset contains parser-generated dependency structures (with POS tags and lemmas) for all FrameNet 1.5 sentences, with nodes automatically associated with FrameNet annotations.