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<Paper uid="C82-2011">
  <Title>GERERALIZED SYNTACTIC RELATIONS AND SUBSTANTIONAL A~TRIBUTES</Title>
  <Section position="1" start_page="0" end_page="0" type="abstr">
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GERERALIZED SYNTACTIC RELATIONS AND SUBSTANTIONAL A~TRIBUTES
Arcady BorkowekY=
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    <Paragraph position="0"> Computing Center, Academy of Sciences, Moscow, USSR The psper presents a conceptual frs~ework for natural lan~age analysis within which some experiments were held and some ideas had been developed.</Paragraph>
    <Paragraph position="1"> The work concerns the means of translation of natural language text into its meaning repreeantation in form of semantic network basing on frwnesdegfo~nsPS1~. The expex~ment~ used Russian as 1spur language.</Paragraph>
    <Paragraph position="2"> I. The analysls is essentially vocabulary driven. Semantto lnfox~attor- Is Intensively used; indeed, the formalism does not make much difference between grammar and sanantPSoe, I% could be regarded as a Generalized syntax., The approach leads tO distribution of words Into classes quite different fx~n usual ~ran-nattoal classes, but having obviously ltnguiBtto. meaning.</Paragraph>
    <Paragraph position="3"> The basic ideas are related with those of /1/, /2/; the earlier variant of vocabulary structure is given in /3/; the Y~iep implementation of vocabulary and semantic network nses property lasts with Inheritance havi~ much in oomaon with PaL, 2. The language description consist of Semantlc and Lexle vocabularies.</Paragraph>
    <Paragraph position="4"> 2.1, The entries of Semantlo Vocabulary are notlons, for~ an abstract sez~utio network for meaning representation &amp;u~ented with gremma~ tnfo~natton, - 49 The vocabulary article contains the following: a) a reference to supernotion! all information from supernotion is relevant to actual notion, if it isn't explicitly euperoeded. The &amp;quot;notion-supernotion&amp;quot; relation imposes hierarchical structure on the set of notions.</Paragraph>
    <Paragraph position="5"> b) a list of the notion's attributes with corresponding Generalized Syntactic Relations (GSR). The set of all GSRs forms the Eralmar used in an~ysis. The GSR attached to attribute must hold for the words (or phrases) of the NL text, the first (master) referring an instance of the notion, the second (slave) referring to the attribute value. E.g. for-Russian, the ~RECEI~ENT attribute of ~GIVE would have a GSR demanding the slave to be an instance of ~PF~SON and to have the form of Dative case. (The dollar sign is used to distin~n~sh notions from words. ) The attributes inherited from supernotion may also have a specification of default or fixed value, which is immediately inserted into meaning representation.</Paragraph>
    <Paragraph position="6"> 2.2. The Lexio Vocabulary contains words. Words can be si~ican% or auxiliary. Significant words are those, which name notions, attributes or attributes values. All other words are au~liary~ they are treated as components of analytic morphological forms and are processed by prescan. Therefore only si~ficant words are present in the vocabulary.</Paragraph>
    <Paragraph position="7"> Lexio Vocabulary article contains:  a) a reference to Semantic Vocabulary with indication of the role cl~s (notionPn~e, attribute-n~ne etc., see below) and, optionally, a lexical function (see /1/)o b) ~ammatical attributes of the word: grammar class, morpholo~cal pattern, fixed grammatical values (such as gender for nouns, aspect for verbs, etc.).</Paragraph>
    <Paragraph position="8"> 3. GSR is a logical function of master's and slave's attributes&amp;quot; values. These can be grammatical attributes from - 50 - null Lexic Vocabulary or provided by presoan, attributes inherited by slave from supernotion or attributes values reflecting the meaning of the text. The most usual ce~es involve matohin 8 slave+s grammatical attributes to some given values or to those of master, and demand for slave to refer a subnotion of a given notion. However some GSRs are more sophisticated. 3.1. The grammar part of GSRs has much in common with Surface Syntactical Relations (3SR) of /1/. Indeed the GSRs had been inspirited by SSRs.</Paragraph>
    <Paragraph position="9"> GSRs differ from SSRs in two aspectsz first, they systematioally use semantic information! second, GSRs usually deal with a deeper syntax level! e,g, if the grammar part of GSR postulates a &amp;quot;direct-object relation&amp;quot;, its description may cover active and passive verbal, participial and nominal oonstructionsz&amp;quot;t0 write a letter&amp;quot;, &amp;quot;a letter is written&amp;quot;, &amp;quot;the letter written by...&amp;quot; and &amp;quot;writting a letter&amp;quot;. 3.2. However, the GSR teohniq~e allows different ~ye.to describe a fra~nent of language~ all depends on the attributes tested. Making the 6ran~ar part of GSRs trivial, one recieves a pure semantic ~asmar. On the other hand, if the set of notions is the set of grammatical classes, GSR~based analysis turns into traditional syntax analysis.</Paragraph>
    <Paragraph position="10"> 3.3. When NL text has been transformed into a set of property lists, fetched from the vocabularies and augmented by morphological preeoan, there are many ways to order the application of the relevant GSRs, for, while each GSR is described procedurally, the description as a whole is declarative. In our experiments a simplification of the parsing algorithm described in /2/ was used.</Paragraph>
    <Paragraph position="11"> 4.1. The outlined approach demands a classification of words different from one based on grammatical classes.</Paragraph>
    <Paragraph position="12"> Significant words are devided into classes depending on the role they play in n~ing corresponding notions. We dieting-51-,. null uish four main classes - N, AY=, A and SA.</Paragraph>
    <Paragraph position="13"> Class N i8 the largest; it is comprised by words which name notionB, instances of notions and venues for some attributes. This class covers most nouns, verbs, verbial ad~ectives and numerals. It also contains a small but very important subclass of pronouns.</Paragraph>
    <Paragraph position="14"> Class AV is formed by words, na~ng attribute together with its value. This class covers most adjectives and adverbs. Class A consists of words naming attributes. Usually they are nounso Example: The followAng words refer the same notion ~FLIGHT in different ways: &amp;quot;to fly&amp;quot;, &amp;quot;flight&amp;quot;, &amp;quot;flyln~ ~ust name it and a~e of the class N; '~peed&amp;quot; is an example of class A, it nsmee an attribute of ~FLIGHT! &amp;quot;quick e and wquAckly&amp;quot; refer to the same attribute, but provide a v~ue (Magn) for it, these two are the me~.ber of class AY=.</Paragraph>
    <Paragraph position="15"> &amp;quot;Simple stories&amp;quot; use mostly N and AV. The words of class A are common in NL-aocess to data-basses 4.2oThe fourth class is formed by Subetantional Attributes (SA). As a matter of fact, their discussion was the main motivation to write this paper. The separation of it from other classes makes it possible to process 88 &amp;quot;linguistio e some text r~lations usually treated as &amp;quot;semantic e and requiring some deductive system to process them.</Paragraph>
    <Paragraph position="16"> Subetantional Attributes combine the properties of the other three classes. They name attribute, provide its value but focusize on an object - the attribute *s value. E.K. &amp;quot;capital&amp;quot; names an attribute of ~OUNTRY, but the focus i8 nor country neither ~he attribute~name but an instance of ~CITY. n attribute has, so to say, its own substantion 'ly separated from the master.</Paragraph>
    <Paragraph position="17"> - 52 -Indeed, unlike attributes of class A, Subetantional Attributes may be used without explicit reference to its master: e,g, &amp;quot;the train goes to the capitePS&amp;quot;. If the master is present, the master-slave relation need not to be expressed syntactically: &amp;quot;Peter ~ave the so.._nn an apple.&amp;quot; Traditional syntax ignores the posessive link between subject (&amp;quot;Peter&amp;quot;) and object (&amp;quot;son&amp;quot;) in this phrase; nor does it consider the previous one incomplete.</Paragraph>
    <Paragraph position="18"> Our GSR-grannnar claims the presence of anaphora in these phrases. ~he first contains an unresolved reverence to some country! in the second one the word &amp;quot;son&amp;quot; includes a reference to some &amp;quot;parent&amp;quot;, the most probably - Peter (i.e. the denotat of &amp;quot;Peter&amp;quot;).</Paragraph>
    <Paragraph position="19"> Defiui tion: A word is Substantial Attribute if it refers an object by naming its relation to some other object or situation. In text Substantional Attribute actfas if it were bound by poseseive relation to a &amp;quot;virtual pronoun&amp;quot; of appropriate semantic class. For example, these two phrases can be yiewed 8~ and &amp;quot;The train goes to the capital Eof-country&amp;quot; &amp;quot;Peter gave hi_.ss son an apple&amp;quot; In the first phrase &amp;quot;1of-country&amp;quot; stands for such a &amp;quot;virtual pronoun&amp;quot;. In the second one, &amp;quot;virtual pronoun&amp;quot; occasionally turned to be a real one; while in English its use is quite natural, in Russian the use of posessive pronoun would have an emphatic meaning.</Paragraph>
    <Paragraph position="20"> The anaphora resolution for such &amp;quot;virtual pronouns&amp;quot; iS done in the same way as for real (lexically expressed) pronouns. However, it is possible to take benefit of the fact, - 53 that &amp;quot;virtual pronoun&amp;quot; refers an instance of specified notion, while for real pronoun only grammatical values ere known. Another example: &amp;quot;President and wife came to capital&amp;quot; (Articles and pronouns ere dropped to reflect Russian), This phrase is processed as &amp;quot;President roof-country with xhis wife came to capital Eofcountry&amp;quot;. null Indeed the wife is the wife of this president, and they came to the city, which is the capital of the country of which he is the president. To infer this from the phrase no extra-linguistic deduction is needed.</Paragraph>
    <Paragraph position="21"> 4.3, The experiments have shown, that treating SAs as two words: one refering an object and another a &amp;quot;virtual pronoun&amp;quot;, is helpful in analysis oriented on extraction of mean-Ing of the text. In fact It deals with a more general question of the limits between &amp;quot;language knowledge&amp;quot; and &amp;quot;knowledge of world&amp;quot;.</Paragraph>
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