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.