Pretrained contextualized embeddings are powerful word representations for structured
prediction tasks. Recent work found that better word representations can be obtained by …

Currently the unified semantic role labeling (SRL) that achieves predicate identification and
argument role labeling in an end-to-end manner has received growing interests. Recent …

Unified opinion role labeling (ORL) aims to detect all possible opinion structures of'opinion-
holder-target'in one shot, given a text. The existing transition-based unified method …

Aspect-based sentiment triplet extraction (ASTE) aims at recognizing the joint triplets from
texts, ie, aspect terms, opinion expressions, and correlated sentiment polarities. As a newly …

Abstract The 2020 Shared Task at the Conference for Computational Language Learning
(CoNLL) was devoted to Meaning Representation Parsing (MRP) across frameworks and …

Constituency parsing and nested named entity recognition (NER) are similar tasks since
they both aim to predict a collection of nested and non-crossing spans. In this work, we cast …

AM dependency parsing is a linguistically principled method for neural semantic parsing
with high accuracy across multiple graphbanks. It relies on a type system that models …

Featured Application Semantic dependency parsing could be applied in many downstream
tasks of natural language processing, including named entity recognition, information …

Dependency parsing aims to extract syntactic dependency structure or semantic
dependency structure for sentences. Existing methods for dependency parsing include …

This paper describes a data-driven framework to parse musical sequences into dependency
trees, which are hierarchical structures used in music cognition research and music …