Dependency Patterns of Complex Sentences and Semantic Disambiguation for Abstract Meaning Representation Parsing

Abstract

The syntax-based AMR parsing approach assumes a close mapping between syntactic and semantic structures. However, syntax-semantic mapping is not evident in complex sentences, causing parsers to fail to build the correct core structure of a tree. In this paper, as an aid to AMR parsing, we propose a dependency matching system that first detects complex sentence structures in a dependency parse tree of a sentence and then returns a corresponding AMR skeleton structure. We manually designed a dictionary of dependency patterns and the corresponding AMR skeletons for the types of complex sentence constructions that appear in the AMR corpus. A disambiguation step is necessary for certain types of constructions with semantically ambiguous subordinators. We show that the disambiguation can be formulated as sentence-pair classification using the fine-tuning approach of a pretrained BERT model. The classification models were trained on data derived from AMR and Wikipedia corpora, establishing a novel baseline for future research.