Deep Dependency Representation
This project provides resources for Deep Dependency Representation (DDR) that integrates deep structure into dependency graphs. The main objective of this project is to develop a dependency representation that is coherent across syntactic variations and gives complete predicate argument structures including non-verbal predicates as well as external arguments. The project is under the Apache 2 license and developed by the Emory NLP research group.
- Deep Dependency Graph Conversion in English. Jinho D. Choi. In Proceedings of the 15th International Workshop on Treebanks and Linguistic Theories, TLT'17, 2017.
- Guidelines for the Clear Style Constituent to Dependency Conversion. Jinho D. Choi and Martha Palmer. Technical Report 01-12, University of Colorado Boulder, 2012.
- Robust Constituent-to-Dependency Conversion for English. Jinho D. Choi and Martha Palmer. In Proceedings of the 9th International Workshop on Treebanks and Linguistic Theories, TLT'10, 2010.
- Retrieving Correct Semantic Boundaries in Dependency Structure. Jinho D. Choi and Martha Palmer. In Proceedings of the 4th Linguistic Annotation Workshop, LAW'10, 2010.
We gratefully acknowledge the support from Kyndi Inc. Any contents in this material are those of the authors and do not necessarily reflect the views of Kyndi Inc.