AMR Parsing
Each AMR is a single rooted, directed graph. AMRs include PropBank semantic roles, within-sentence coreference, named entities and types, modality, negation, questions, quantities, and so on. See.
Papers
Showing 1–10 of 117 papers
Benchmark Results
| # | Model | Metric | Claimed | Verified | Status |
|---|---|---|---|---|---|
| 1 | APT (IBM) | F1 Full | 78.5 | — | Unverified |
| 2 | stack-Transformer + self-learning (IBM) | F1 Full | 78.2 | — | Unverified |
| 3 | AMR Parsing via Graph-Sequence Iterative Inference | F1 Full | 75.4 | — | Unverified |
| 4 | Broad-Coverage Semantic Parsing as Transduction | F1 Full | 71.3 | — | Unverified |
| 5 | Two-stage Sequence-to-Graph Transducer | F1 Full | 70.2 | — | Unverified |
| 6 | Imitation learning | F1 Newswire | 70 | — | Unverified |
| 7 | Transition-based+improved aligner+ensemble | F1 Full | 68.4 | — | Unverified |
| 8 | Improved CAMR | F1 Full | 68.1 | — | Unverified |
| 9 | Transition-based transducer | F1 Full | 66 | — | Unverified |
| 10 | Incremental joint model | F1 Full | 66 | — | Unverified |