Non-Deterministic Segmentation for Chinese Lattice Parsing

Abstract

Parsing Chinese critically depends on correct word segmentation for the parser since incorrect segmentation inevitably causes incorrect parses. We investigate a pipeline approach to segmentation and parsing using word lattices as parser input. We compare CRF-based and lexicon-based approaches to word segmentation. Our results show that the lattice parser is capable of selecting the correction segmentation from thousands of options, thus drastically reducing the number of unparsed sentence. Lexicon-based parsing models have a better coverage than the CRFbased approach, but the many options are more difficult to handle. We reach our best result by using a lexicon from the nbest CRF analyses, combined with highly probable words.

Detecting Syntactic Features of Translated Chinese

“…and for specific genres. It is also desirable to improve the accuracy of constituent parsers for Chinese, along the lines of (Wang et al, 2013;Wang and Xue, 2014;Hu et al, 2017), since accurate syntactic trees are the prerequisite for accurate feature interpretation. While the parser in this study works well, better parsers will undoubtedly be a plus.…”

Proceedings of the Second Workshop on Stylistic Variation

“…and for specific genres. It is also desirable to improve the accuracy of constituent parsers for Chinese, along the lines of Wang and Xue, 2014;Hu et al, 2017), since accurate syntactic trees are the prerequisite for accurate feature interpretation. While the parser in this study works well, better parsers will undoubtedly be a plus.…”