A Differentiable Relaxation of Graph Segmentation and Alignment for AMR Parsing. (arXiv:2010.12676v2 [cs.CL] UPDATED)

Abstract Meaning Representations (AMR) are a broad-coverage semantic
formalism which represents sentence meaning as a directed acyclic graph. To
train most AMR parsers, one needs to segment the graph into subgraphs and align
each such subgraph to a word in a sentence; this is normally done at
preprocessing, relying on hand-crafted rules. In contrast, we treat both
alignment and segmentation as latent variables in our model and induce them as
part of end-to-end training.

As marginalizing over the structured latent …

alignment amr arxiv graph parsing segmentation