Abstract

There are few corpora that endeavor to represent the semantic content of entire documents. We present a corpus that accomplishes one way of capturing document level semantics, by annotating coreference and similar phenomena (bridging and implicit roles) on top of gold Abstract Meaning Representations of sentence-level semantics. We present a new corpus of this annotation, with analysis of its quality, alongside a plausible baseline for comparison. It is hoped that this Multi-Sentence AMR corpus (MS-AMR) may become a feasible method for developing rich representations of document meaning, useful for tasks such as information extraction and question answering.

Date

2018

Authors

Tim O’Gorman, Michael Regan, Kira Griffitt, Ulf Hermjakob, Kevin Knight, Martha Palmer

Conference

Proceedings of the 27th international conference on computational linguistics

Pages

3693-3702