On Sat, Feb 9, 2019 at 4:22 AM Ben Goertzel <b...@goertzel.org> wrote:
> > We are now playing with hybridizing these symbolic-ish grammar > induction methods with neural net language models, basically using the > predictive models produced by models in the BERT lineage (but more > sophisticated than vanilla BERT) in place of simple mutual information > values to produce more broadly-context-sensitive parse choices in > Linas's MST parser... > This last sentence suggests that the near-total confusion about MST continues to persist in the team. I keep telling them to collect the statistics, and then discard the MST parse **immediately**. Trying to "improve" MST is a total waste of time. Seriously: Instead, try skipping the MST step entirely. Just do not even do it, AT ALL. Rip it out. It is NOT a step that the algorithm even needs. I'll bet you that if you skip the MST step completely, the quality of your results will be more-or-less unchanged. The results might even get better! If your results don't change, by skipping MST, or if your results get better, by skipping MST, then that should be a clear indicator that trying to "improve" MST is a waste of time! -- Linas -- cassette tapes - analog TV - film cameras - you ------------------------------------------ Artificial General Intelligence List: AGI Permalink: https://agi.topicbox.com/groups/agi/Ta6fce6a7b640886a-M843d12260f98baeb7e8413e0 Delivery options: https://agi.topicbox.com/groups/agi/subscription
