Direct parsing to sentiment graphs

TL;DR

This paper introduces a graph-based semantic parser that directly predicts sentiment graphs from text, achieving state-of-the-art results on multiple benchmarks and providing open-source resources.

Contribution

It presents a novel approach for structured sentiment analysis using direct graph parsing, advancing the state of the art.

Findings

Outperforms previous methods on 4 of 5 benchmark datasets

Provides open-source code, models, and predictions

Demonstrates effectiveness of graph-based sentiment parsing

Abstract

This paper demonstrates how a graph-based semantic parser can be applied to the task of structured sentiment analysis, directly predicting sentiment graphs from text. We advance the state of the art on 4 out of 5 standard benchmark sets. We release the source code, models and predictions.