Papers with parser accuracy
Representing Schema Structure with Graph Neural Networks for Text-to-SQL Parsing (P19-1)
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| Challenge: | Semantic parsing to SQL has largely ignored the structure of the database schema . a recent study used a simple DB that was observed at both training and test time. |
| Approach: | They propose a semantic parser where the schema structure is encoded with a graph neural network and used at both encoding and decoding time. |
| Outcome: | The proposed parser improves from 33.8% to 39.4%, dramatically above the current state of the art, which is at 19.7%. |
Revisiting Supertagging for faster HPSG parsing (2024.emnlp-main)
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| Challenge: | a new supertagger for HPSG-based treebanks is used to improve parsing speed and accuracy. |
| Approach: | They propose to integrate the best supertagger into an HPSG-based parser and compare it to an existing system. |
| Outcome: | The proposed system achieves 97.26% accuracy on 950 sentences from WSJ23 and 93.88% on the out-of-domain technical essay The Cathedral and the Bazaar. |