[comp.ai.nlang-know-rep] NL-KR Digest Volume 5 No. 3

nl-kr-request@CS.ROCHESTER.EDU (NL-KR Moderator Brad Miller) (07/28/88)

NL-KR Digest             (7/27/88 20:03:00)            Volume 5 Number 3

Today's Topics:
        wanted: GPSG parser
        FUG as an AI language.
        Poltergeist
        Small on-line dictionary (or English nouns & verbs) sought 
        Chomsky awarded Kyoto Prize in basic sciences
        text-to-speech, text-to-phoneme, or text-to-syllable algorithms
        Implementing dictionaries
        
Submissions: NL-KR@CS.ROCHESTER.EDU 
Requests, policy: NL-KR-REQUEST@CS.ROCHESTER.EDU
----------------------------------------------------------------------

Date: Tue, 12 Jul 88 11:25 EDT
From: COR_HVH%HNYKUN52.BITNET@CUNYVM.CUNY.EDU
Subject:  wanted: GPSG parser

A colleague of mine, Vera Kamphuis, asked me to post the following
request:

========================================================================

    In a recently started teaching program at the Department of Language
and Speech, University of Nijmegen, the Netherlands, one of the courses
deals with formal grammars. Different formalisms are presented to the
students, and practical sessions serve to give them some experience in
using these formalisms.

     One of the grammatical models discussed in this course is GPSG.
However, the problem in last year's course was that no practical
facilities were available, as a result of which students found it
difficult to grasp the essence of the formalism. Our question is:
Can anyone tell us whether a GPSG-parser(-generator) is available
somewhere and if so, how we might be able to get our hands on it? As
was said above, it serves only to give students the possibility to
become acquainted with the practical use of the formalism, so it does
not matter if it can only handle small-size grammars, for example.
What is important is that it has workable speed.

======================================================================

Any information can be posted or sent to me at COR_HVH @ HNYKUN52 on
BITNET. I will post a compilation of direct answers at the end of August
or when the first one comes in (whatever's later).

Thanks,
  Hans van Halteren


------------------------------

Date: Thu, 14 Jul 88 14:54 EDT
From: Jonas Mellin <mcvax!cs.exeter.ac.uk!jme@uunet.UU.NET>
Subject: FUG as an AI language.


I am a M.Sc student in computer science and I have started on my project.
I have come to a choice in the project. I want to investigate FUG
(Functional Unification Grammar) as a PROLOG like AI language.

Has anybody investigated FUG as an AI language?

Thanks,
Jonas

------------------------------

Date: Mon, 18 Jul 88 18:16 EDT
From: TALMAGE%VUVAXCOM.BITNET@CUNYVM.CUNY.EDU
Subject:  Poltergeist


Poltergeist, as I recall, is a workstation-based tool for teaching foreign
languages.  The user types commands in some language, French, for example,
and the Poltergeist inside the workstation rearranges the room pictured on
the workstation accordingly.  The user might say, "Turn the table upside
down and put the vase upside down on one of the legs."

Not long ago I read an article about this tool.  I'd like to reread the
article but can't find it in my library.  It was in, I think,
_Technological Horizons in Education Journal_.  The people responsible for
the article and the software are from MIT, I think.

Can anyone point me to anything in print on this?

Thanks.

______________________________________________________________________________

David W. Talmage / Villanova U / University Computing and Information Services
UUCP:   ...!vu-vlsi!excalibur!talmage
Bitnet: talmage@vuvaxcom         <best choice>
Arpa-gate:   talmage%vuvaxcom.bitnet@your-favorite-gateway

------------------------------

Date: Mon, 25 Jul 88 01:57 EDT
From: ERIC Y.H. TSUI <munnari!aragorn.oz.au!eric@uunet.UU.NET>
Subject: Small on-line dictionary (or English nouns & verbs) sought 

Would anyone has access to an electronic copy of English nouns and verbs ?
A small (500 entries) to medium collection (5000 entries) would be appropriate.
It would be ideal if the verbs (and/or nouns) are grouped into various 
categories. I am also prepared to work with a small on-line dictionary and
manually extract the required knowledge.

The knowledge is sought for the design of lexicon and semantic knowledge 
for a restricted NL front end (for encoding rules).

Eric Tsui                               eric@aragorn.oz
Division of Computing and Mathematics
Deakin University
Geelong, Victoria 3217
AUSTRALIA

------------------------------

Date: Mon, 25 Jul 88 15:05 EDT
From: Bob Freidin <bob@mind.UUCP>
Subject: Chomsky awarded Kyoto Prize in basic sciences


On June 24th the Inamori Foundation of Japan announced the recipients of
this year's Kyoto Prizes.  

	Basic Sciences:  Noam Chomsky (for contributions to Linguistics)

	Advanced Technology:  John McCarthy (for pioneering in Artificial
				   Intelligence)

	Creative Arts and Moral Sciences:  Paul Thieme (for contributions 
					to the history of Indian philosophy)

Each recipient will receive a prize of 45 million yen (approx. $350,000).
This is the fourth year these prizes, characterized as Japan's version of 
the Nobel, have been awarded.  Kyoto Prize Laureates in the first two areas 
include:

		Basic Sciences		Advanced Technology

 	1985:	Claude E. Shannon 	Rudolf Emil Kalman
        1986:	George E. Hutchinson	Nicole M. Le Douarin
	1987:   Jan H. Oort		Morris Cohen

++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++

Robert Freidin
Director
Program in Linguistics
Princeton University

------------------------------

Date: Sun, 24 Jul 88 19:31 EDT
From: Walter Rolandi <rolandi@gollum.UUCP>
Subject: text-to-speech, text-to-phoneme, or text-to-syllable algorithms


Thanks to all those who responded to my request for ways to identify 
the syllables of English.  Several people suggested text-to-speech
algorithms but no one has offered to provide one.  Does anyone have a 
text-to-speech algorithm that they would be willing to post?  I am sure
many people would be interested.

Thanks.

Walter Rolandi
rolandi@ncrcae.UUCP 
rolandi@ncrcae.Columbia.NCR.COM
NCR Advanced Systems Development, Columbia, SC

------------------------------

Date: Fri, 22 Jul 88 17:46 EDT
From: TALMAGE%VUVAXCOM.BITNET@CUNYVM.CUNY.EDU
Subject:  Implementing dictionaries

The Background Information:

This year I'm enrolled in the Esperanto Postal Course given for free by the
Esperanto League for North America.  The language Esperanto seems much
easier to learn than French was for me;  I feel as though I can do more with
Esperanto after the first three lessons than I could with French after a
year of lessons.  Some of this, I suppose, may be because I've already some
background in learning languages.  The second one is supposed to be easier
than the first.

Along with the Postal Course, I've decided to see how far I can go in using
my computer to translate Esperanto into English.  I'm doing this work in
Icon and it's progressing very quickly.  Already the software can recognize
the part of speech of most of the words in the vocabulary.  It can, on my
Amiga, pronounce those words as well.

For now, I'm content to go with a word-for-word translation.  I've seen the
recent postings of wfw translations of Chinese, Hungarian(?), Dutch, and
"WeirdSpeak" in NL-KR Digest and am amused.  A more robust method of
translation will come around once I learn more about Esperanto and machine
translation.



The Query:

I'm about ready to implement a dictionary and would like to hear from
people with ideas about this.  Book references would be fine, as would
suggestions from people who are doing something like this.

Here is a version of the dictionary I may implement.  It's perhaps too
simple, not accounting for some kinds of idioms, but I think it will work.


This is what each entry in the dictionary will look like.

        record Entry( PartOfSpeech, SemanticList )
        record Semantic( Attributes, DefinitionList )


The dictionary will be a table whose entry values are root words and whose
assigned values are lists of Entry.  There will be at most one Entry per
PartOfSpeech.  For each PartOfSpeech there will be a list of semantic
components, SemanticList.  Each Semantic has a unique set of Attributes and
a list of definitions that apply to words with those attributes.


This is what part of the the dictionary entry for the root "ami" will look
like.  It is incomplete, of course.  There are several other attributes for
the verbs and I've left out the entries for adjectives and adverbs.


        Dictionary[ "ami" ] :=
          [ Entry( noun, [ Semantic( singular + male, ["friend",
                                                       "male friend"] ),
                           Semantic( singular + female, ["friend",
                                                         "female friend"] ),
                           Semantic( plural + male, ["friends",
                                                     "female friends"] ),
                           Semantic( plural + female, ["friends",
                                                        "female friends"] )
                         ]
                 ),
            Entry( verb, [ Semantic( infinitive, ["to love"] ),
                           Semantic( present, ["love", "loves"] ),
                           Semantic( past, ["loved"] ),
                           Semantic( future, ["will love", "shall love" ] )
                         ]
                 )
          ]




To find the word "amikino", which means "female friend", in the dictionary,
we find its part of speech and its attributes by removing the grammar coded
suffixes.  "O" comes first and tells us we have a noun.  "In" gives us the
attributed for female.  There is another rule for removing the "k" but I
don't know what it is yet.  I suspect there is a general rule for making
nouns from root verbs.

So now we've removed "kino", leaving us with the root word "ami", which is
also, I think, the infinitive form of the verb, to love.  Next we look in
the dictionary for "ami" and we find that list of Entries.  In the first
Entry, we see the PartOfSpeech noun so we search its list of Semantics
until we find one with the Attributes female.  This gives us the list of
possible definitions "friend" and "female friend".


With kind regards,

David Talmage

______________________________________________________________________________

David W. Talmage / Villanova U / University Computing and Information Services
UUCP:   ...!vu-vlsi!excalibur!talmage
Bitnet: talmage@vuvaxcom         <best choice>
Arpa-gate:   talmage%vuvaxcom.bitnet@your-favorite-gateway

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End of NL-KR Digest
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