On Sun, May 5, 2019 at 10:15 PM Anton Kolonin @ Gmail <[email protected]>
wrote:

> Hi Linas, I am re-reading your emails and updating our TODO issues from
> some of them.
>
> Not sure about this one:
> >Did Deniz Yuret falsify his thesis data? He got better than 80% accuracy;
> we should too.
>
> I don't recall Deniz Yuret comparing MST-parses to
> LG-English-grammar-parses.
>


Linas: Where does the > 80% figure come from?

This paper of Yuret's

http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.129.5016&rep=rep1&type=pdf

cites 53% accuracy compared against "dependency parses derived from
dependency-grammar-izing Penn Treebank parses on WSJ text" ....   It was
written after his PhD thesis.  Is there more recent work by Yuret that
gives massively better results?  If so I haven't seen it.

Spitkovsky's more recent work on unsupervised grammar induction seems to
have gotten better statistics than this, but it used radically different
methods.


>
> a) Seemingly "worse than LG-English" "sequential parses" provide seemingly
> better "LG grammar" - that may be some mistake, so we will have to
> double-check this.
>

Anton -- Have you looked at the inferred grammar for this case, to see how
much sense it makes conceptually?

Using sequential parses is basically just using co-occurrence rather than
syntactic information

I wonder what would happen if you used *both* the sequential parse *and*
some fancier hierarchical parse as inputs to clustering and grammar
learning?   I.e. don't throw out the information of simple before-and-after
co-occurrence, but augment it with information from the statistically
inferred dependency parse tree...




-- Ben

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