Bottom-Up Unranked Tree-to-Graph Transducers for Translation into Semantic Graphs
Johanna Björklund, Shay B. Cohen, Frank Drewes, Giorgio Satta
Abstract
We propose a formal model for translating unranked syntactic trees, such as dependency trees, into semantic graphs. These tree-to-graph transducers can serve as a formal basis of transition systems for semantic parsing which recently have been shown to perform very well, yet hitherto lack formalization. Our model features “extended” rules and an arc-factored normal form, comes with an efficient translation algorithm, and can be equipped with weights in a straightforward manner.- Anthology ID:
- W19-3104
- Volume:
- Proceedings of the 14th International Conference on Finite-State Methods and Natural Language Processing
- Month:
- September
- Year:
- 2019
- Address:
- Dresden, Germany
- Editors:
- Heiko Vogler, Andreas Maletti
- Venue:
- FSMNLP
- SIG:
- SIGFSM
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 7–17
- Language:
- URL:
- https://aclanthology.org/W19-3104
- DOI:
- 10.18653/v1/W19-3104
- Cite (ACL):
- Johanna Björklund, Shay B. Cohen, Frank Drewes, and Giorgio Satta. 2019. Bottom-Up Unranked Tree-to-Graph Transducers for Translation into Semantic Graphs. In Proceedings of the 14th International Conference on Finite-State Methods and Natural Language Processing, pages 7–17, Dresden, Germany. Association for Computational Linguistics.
- Cite (Informal):
- Bottom-Up Unranked Tree-to-Graph Transducers for Translation into Semantic Graphs (Björklund et al., FSMNLP 2019)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-1/W19-3104.pdf