Direct parsing to sentiment graphs
About
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.
David Samuel, Jeremy Barnes, Robin Kurtz, Stephan Oepen, Lilja {\O}vrelid, Erik Velldal• 2022
Related benchmarks
| Task | Dataset | Result | Rank | |
|---|---|---|---|---|
| Structured Sentiment Analysis | NoReC v1.0 (test) | Holder Span F165.1 | 5 | |
| Structured Sentiment Analysis | CA v1.0 (test) | Holder Span F160.8 | 5 | |
| Structured Sentiment Analysis | MPQA v1.0 (test) | Holder Span F158.4 | 5 | |
| Structured Sentiment Analysis | EU v1.0 (test) | Holder Span F164.2 | 5 | |
| Structured Sentiment Analysis | DSU v1.0 (test) | Holder Span F142.2 | 5 |
Showing 5 of 5 rows