Faster Shift-Reduce Constituent Parsing with a Non-Binary, Bottom-Up Strategy 1footnote 11footnote 1© 2019. This is the final peer-reviewed manuscript that was accepted for publication at Artificial Intelligence and made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/. This may not reflect subsequent changes resulting from the publishing process such as editing, formatting, pagination, and other quality control mechanisms. The final journal publication is available at https://doi.org/10.1016/j.artint.2019.07.006.
Table 7: F-score on constituents with a number of children ranging from one to five on WSJ §23.
['Parser', '#1', '#2', '#3', '#4', '#5']
We undertake a structure analysis to get insight into why our non-binary system is outperforming the binary version when the latter benefits from a prior binarization (which simplifies the initial problem and provides head information). We use the variant of our transition system trained by a static oracle to carry out a fair comparison. From the results, we can state that the proposed non-binary shift-reduce parser improves over the binary one not only on more-than-binary branches, but also in unary and binary structures.