[musesum]

> The statistics listed on the project GitHub actually contradict these claims by showing the original March 2016 implementation has higher accuracy than Parsey McParseface.

So you're referring to this LSTM?

"Andor et al. (2016)* is simply a SyntaxNet model with a larger beam and network. For futher information on the datasets, see that paper under the section "Treebank Union"."

After spending a few months hand coding a NLP parser, am rather intrigued by LSTM. I like the idea of finding coefficients, as opposed to juggling artificial labels.

[xigency]

Yes, my mistake. Their claim is that SyntaxNet (originally described in the paper and improved over one month) is the best in field, whereas Parsey McParseface is just one trained instance.

[musesum]

> SyntaxNet improved over one month ... whereas Parsey McParseface is just one trained instance

Cool. I wonder how much how much Human effort (vs machine time) went into tweaking SyntaxNet versus tweaking Parsey M.?