Papers with graph-aware sequence model
Semantic graph parsing with recurrent neural network DAG grammars (D19-1)
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| Challenge: | Semantic parsing is the task of mapping natural language to machine interpretable meaning representations. |
| Approach: | They propose a graph-aware sequence model that generates only well-formed graphs . their model is based on a multilingual semantic graphbank . |
| Outcome: | The proposed model yields competitive results in English and establishes the first results for German, Italian and Dutch. |
Accurate polyglot semantic parsing with DAG grammars (2020.findings-emnlp)
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| Challenge: | Semantic parsers treat graphs as strings or trees, but there is no guarantee that the output is a well-formed graph. |
| Approach: | They propose a graph-aware sequence model that utilizes a DAG grammar to guide graph generation. |
| Outcome: | The proposed model outperforms string-based and DAG-grammar models by a large margin and can guarantee the well-formed graphs. |