[developers] Using the ERG for research

[goodman.m.w at gmail.com]

Hello Matthew,

I can offer a prototype using PyDelphin v0.9.2. The following Python 3 code
assumes you have PyDelphin (https://github.com/delph-in/pydelphin) and ACE (
http://sweaglesw.org/linguistics/ace/) installed and a copy of the ERG .dat
file (from ACE's website).

First, if you want to detect types in the syntax like 'v_dat_dlr', you
probably want to look through the derivation tree. The following function
descends through the tree and looks for the type:

    from delphin import derivation

    def find_v_dat_dlr(d):
        if isinstance(d, derivation.UdfNode):
            if d.entity == 'v_dat_dlr':
                return d.terminals()
            else:
                xs = []
                for dtr in d.daughters:
                    xs.extend(find_v_dat_dlr(dtr))
                return xs
        else:
            return []

This function could probably be improved but it seems to work for now.

Now if you want to parse a sentence, generate from its MRS, and inspect
each derivation tree, you can do this:

    from delphin.interfaces import ace

    grm = '/home/mwg/grammars/erg-2018-x86-64-0.9.30.dat'  # adjust as
necessary
    sent = 'The gracious hostess offered the special guest her seat.'
    parse_response = ace.parse(grm, sent)
    first_result = parse_response.result(0)
    mrs = first_result['mrs']

    gen_response = ace.generate(grm, mrs)
    if gen_response:
        for result in gen_response.results():
            drv = result.derivation()
            dative_terminals = find_v_dat_dlr(drv)
            if dative_terminals:
                print(result['surface'])
                print('  ({})'.format(
                    ', '.join(tml.form for tml in dative_terminals)))
                print()

Running this prints matching sentences and the token that went through the
dative lexical rule.

    Her seat was offered by the gracious hostess to the special guest.
      (offered)

    The gracious hostess offered her seat to the special guest.
      (offered)

I hope that is enough to get started.

On Tue, Jul 2, 2019 at 3:59 AM Alexandre Rademaker <arademaker at gmail.com>
wrote:

> Hi Matthew,
>
> Maybe someone with more experience than me can add something here, but as
> far as I remember from the LREC tutorial in 2016, we can easily make a
> pipeline of two ACE calls.
>
> I also found this page http://moin.delph-in.net/AceUse
>
>
> $ cat test.txt
> The gracious hostess offered the special guest her seat.
>
> $ cat test.txt  | ~/hpsg/ace/ace -g ~/hpsg/ace/erg.dat -Tf1 |
> ~/hpsg/ace/ace -g ~/hpsg/ace/erg.dat -e
> NOTE: 1 readings, added 2940 / 844 edges to chart (306 fully instantiated,
> 210 actives used, 238 passives used) RAM: 7523k
> NOTE: parsed 1 / 1 sentences, avg 7523k, time 0.04242s
> Her seat was offered by the gracious hostess to the special guest.
> The gracious hostess offered her seat to the special guest.
> The special guest was offerred her seat by the gracious hostess.
> The gracious hostess offered the special guest her seat.
> NOTE: 1063 passive, 833 active edges in final generation chart; built 1264
> passives total. [4 results]
>
> NOTE: generated 1 / 1 sentences, avg 13582k, time 0.10198s
> NOTE: transfer did 1025 successful unifies and 992 failed ones
>
>
> Using http://pydelphin.readthedocs.io may be easier to collect the
> outputs and control the interaction.
>
>
> Best,
>
>
> --
> Alexandre Rademaker
> http://arademaker.github.io
>
>
> > On 1 Jul 2019, at 13:34, Ann Copestake <aac10 at cl.cam.ac.uk> wrote:
> >
> > in case anyone has time to respond to Matthew
> >
> >
> > -------- Forwarded Message --------
> > Subject:      Using the ERG for research
> > Date: Fri, 28 Jun 2019 17:12:35 -0400
> > From: Matthew Kelly <mak582 at psu.edu>
> > To:   lingo at delph-in.net
> >
> >
> > Dear LinGO lab,
> >
> > I'm a post-doctoral researcher at Penn State looking to use your ERG
> software package to convert a few thousand dative double object sentences
> into dative prepositional object sentences and vice versa.
> >
> > For example, I'd like to convert the prepositional object sentence "The
> gracious hostess offered her seat to the special guest." to the double
> object sentence "The gracious hostess offered the special guest her seat."
> >
> > I am able to perform this conversion by using the online interface to
> "analyze" a sentence and then pressing "generate" to produce alternatives.
> How could I do this in batch, automatically?
> >
> > Thank you,
> > Matthew.
> >
> > --
> > Matthew A. Kelly, Ph.D.
> > E370 Westgate Building
> > College of Information Sciences and Technology
> > The Pennsylvania State University
> >
>
>
>

-- 
-Michael Wayne Goodman
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