CLSep 12, 2014
Incorporating Semi-supervised Features into Discontinuous Easy-First Constituent Parsing
arXiv:1409.3813v110 citations
Originality Synthesis-oriented
AI Analysis
This work addresses parsing challenges for multiple languages in NLP, but it is incremental as it builds on existing methods.
The paper adapted the EaFi parser for discontinuous constituent parsing to multiple languages and utilized unlabeled data from the SPMRL 2014 shared task, resulting in unspecified performance improvements.
This paper describes adaptations for EaFi, a parser for easy-first parsing of discontinuous constituents, to adapt it to multiple languages as well as make use of the unlabeled data that was provided as part of the SPMRL shared task 2014.