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<?xml version="1.0" standalone="yes"?> <Paper uid="C65-1022"> <Title>SENTENCE GENERATION BY SEMANTIC CONCORDANCE</Title> <Section position="4" start_page="22" end_page="22" type="metho"> <SectionTitle> 3. SENTENCE GENERATION BY SEMANTIC CONCORDANCE </SectionTitle> <Paragraph position="0"> We concentrate our efforts on the generation of the affirmative active declarative sentences. We try to generate this kernel sentence by the expansion rules. By the generation of the kernel sentence the attention is on the structural balance of the whole sentence, the influence of the choice of a word to the other part of the phrase, and their relation to the unified concept of the sentence. An expansion rule has a main constituent and the other non-main constituents in the expanded part. The latter symbols may contain optional elements.</Paragraph> <Paragraph position="1"> When an expansion rule is applied to a non-terminal symbol, to which there is already given a concrete word, the word is assigned to the main constituent of the expanded part. The words to the non-main constituent symbols are selected in relation to the main constituent word. A verb or a noun is taken as the main constituent of the non-terminal symbol &quot;sentence&quot; (initial symbol).</Paragraph> <Paragraph position="3"> A set of P's belonging to a word w</Paragraph> <Paragraph position="5"> The type of expansion rules: z --~2~ , z eZ : string of symbols in M. (lis called a syntactic unit)</Paragraph> <Paragraph position="7"> left to right to the non-main constituents of string ~ .</Paragraph> <Paragraph position="8"> If ~is composed of only one symbol, there is no non-main constituent.</Paragraph> <Paragraph position="9"> Optional elements in the expansion rules are indicated by a pair of brackets attached to the symbols. An optional element in ~ can not be the main constituent.</Paragraph> <Paragraph position="10"> The type of selection rules: s-* w or s ~-~w Semi-terminal derivation: Expansion rules are applied on non-terminal symbols, to the stage where there is no symbol to be expanded. The final string is composed of SWC. A set of the derived main constituents for a symbol z: A set of all the SWC which can be the main constituent of a non-terminal symbol z or the main constituents of a phrase which is generated by successive expansions of the main constituents of the original z.</Paragraph> <Paragraph position="12"/> <Section position="1" start_page="22" end_page="22" type="sub_section"> <SectionTitle> 3.2 The process of generation of a kernel sentence (I) </SectionTitle> <Paragraph position="0"> We suppose that a sentence has one central thing or concept to be mentioned first of all. This is the main constituent of a sentence. Then a second important concept is determined with its grammatical position, referring to the central concept already selected. Next a third important one is determined likewise, and so on. This process is formally represented in the following.</Paragraph> <Paragraph position="1"> (i) Zo +~ w(s~ (Zo)) s~(zo) is an element of S(zo) which is the set of the derived main constituents for zo. W(SL(Zo)) is a word belonging to the set W(s~(zo)). This shows the process starts from the selection of a word w for the axiom z o , and the sentence is to be constructed with the core word w.</Paragraph> <Paragraph position="2"> (ii) z0-~ , if sPS(z,)6S(MCZ)) The axiom z o can be expanded into the syntactic unit ~ if and only if the already selected s{(zo) at the stage (i) is contained in the set of the derived main constituents for M(~).</Paragraph> <Paragraph position="3"> (iii) M(~)*-*wCsz(zo)) The already selected word w(sL(za)) is assigned to the main constituent M(2~) of the expanded syntactic unitl.</Paragraph> <Paragraph position="4"> (iv) NMk(~)*-~ w~se~CNSk(2))), for an k.</Paragraph> <Paragraph position="5"> if a certain condition C' PC~A P (~,.t.), P(w:,; :t &quot;&quot;' ) is satisfied.</Paragraph> <Paragraph position="6"> To each non-main constituents NMk(~) is corresponded each word w~ if the semantic categories for the words have a certain relation fz with that of the word w assigned to M(~).</Paragraph> <Paragraph position="7"> Sakai & Nagao 5 At the n-th stage of the generation: It is supposed that a word is already assigned to the symbol.</Paragraph> <Paragraph position="9"> is satisfied.</Paragraph> </Section> <Section position="2" start_page="22" end_page="22" type="sub_section"> <SectionTitle> 3.3 Condition~ </SectionTitle> <Paragraph position="0"> To all the elements of the semantic categories P = (Pl, P2' &quot;'&quot; ), the semantic distances are supposed to be defined.</Paragraph> <Paragraph position="2"> An example of this process is illustrated in Fig. I. The double line indicates the main constituent of a phrase symbol which is written one line above.</Paragraph> <Paragraph position="3"> Certain semantic conditions are imposed on the pair of phrase names in a phrase, which are underlined.</Paragraph> </Section> <Section position="3" start_page="22" end_page="22" type="sub_section"> <SectionTitle> 3.4 The process of generation of a kernel sentence (II) </SectionTitle> <Paragraph position="0"> The generation process explained in 3.2 is from the axiom. But there are the cases where we want to construct a sentence from arbitrary grammatical positions and a given word. For example when we write a complex sentence like &quot;The old gentleman whom we saw at the theatre was his father.&quot;, the main constituent of the subordinate clause is not &quot;gentleman&quot;, but the verb &quot;saw&quot;. So we must generate a sentence from a noun &quot;gentleman&quot; and its grammatical position: objective case.</Paragraph> <Paragraph position="1"> The process is that first the start point of generation is given by a word and its part of speech in a sentence. Next we select a proper rewriti~m rule which contains the part of speech of the word selected Just now. Then to the remaining elements of the rewritten phrase the proper words are assigned, the semantic categories of which coincide with the one of the alread~ selected word. This process is continued as far as there remains no element which can be rewritten by a phrase. The process is formally represented in the following.</Paragraph> <Paragraph position="2"> (i) Given z, w, s, where s4-~w, s e S(z) (ii) A tree structure whose top symbol is z is constructed by the method explained in 3.2.</Paragraph> <Paragraph position="3"> (iii) z'--~ ~ , Z = fz,'~ .... z-.. 2z~.</Paragraph> <Paragraph position="4"> A phrase z' is selected which contains z as a component of the expansion rule ~'-~2.</Paragraph> <Paragraph position="5"> Sakai & Nagao 6 (iv) z+~w, Pz:*-~, i = 1,2, ...... ,n where certain condition is satisfied.</Paragraph> <Paragraph position="6"> A proper word is corresponded to each phrase P~.</Paragraph> <Paragraph position="7"> (v) Tree structures whose top symbols are Pz~ (i = 1,2, ... ) are constructed for all ~ by the method mentioned in 3.2.</Paragraph> <Paragraph position="8"> (vi) At the stage (iii), z' is newly replaced by z and the same operations from stage (iii) to (v) are performed.</Paragraph> <Paragraph position="9"> (vii) When z' = zo(axiom) is reached and the steps (iv) to (v) are completed, then the whole tree is accomplished under the axiom z o.</Paragraph> <Paragraph position="10"> An example of this process is illustrated in Fig. 2. The direction indicates the steps the sentence is constructed.</Paragraph> </Section> </Section> <Section position="5" start_page="22" end_page="22" type="metho"> <SectionTitle> 4. TRANSFORMATIONAL RULES </SectionTitle> <Paragraph position="0"/> <Section position="1" start_page="22" end_page="22" type="sub_section"> <SectionTitle> 4.1 Representation of the rules </SectionTitle> <Paragraph position="0"> The transformational rules can explain many sentence structures which are difficult to treat in an immediate constituent method. For example in the sentence &quot;Is he young?&quot;, which is a question form of &quot;He is young&quot;, &quot;is young&quot; becomes discontinuous, separated by &quot;he&quot;. This is difficult to treat by an immediate constituent method. It is far more natural to explain this by the application of a transformational rule concerning question to the original affirmative sentence.</Paragraph> <Paragraph position="1"> The transformational rules we are now utilizing are classified to three types. The type 1 is unary transformations which may be thought of as converting a sentence from one to another, The type 2 is binary transformations which combine two sentences to form a third. And the type 3 is a transformation between two phrases. In all these cases we can formally represent the transformational rules as the following type.</Paragraph> <Paragraph position="2"> z : XI'X~ ....... X~-~y l&quot; X~,-yI&quot; X~y .......... y~.X~y~+~. (I) The symbol z which is written on the left side means that this transformational rules should be applied to the phrase z. Xi, Xs, ..... , X~are either the elements of M or words themselves. Among them we have a special symbol ~, which indicates that for this symbol ~, there might or might not correspond some term in a~investigated phrase z * That is, ~ expresses an arbitrary term. Y,, Y:, ..... , Y~i are vacant, some symbols or words which are not equal to X |, X~, ..... , X,. XL, , X~,, ...... , X~ are some symbols among Xi, XA, ..... , X~.</Paragraph> <Paragraph position="3"> The phrase z may have an internal tree structure, so the transformational rule is applied to this tree. An example of this is illustrated in Fig. 3.</Paragraph> <Paragraph position="4"> In this figure a noun phrase &quot;the red books&quot; is transformed to another noun phrase &quot;the books which are red&quot;. This transformation is done by the rule, NPI: ~.AD.NQ ---~@-NQ-WHICH BE.AD There are problems in the transformational rules such as follows.</Paragraph> <Paragraph position="5"> (i) We have no definite criteria as to what kind of sentence structure is Sakai & Nagao 7 to be treated in the scope of phrase structure grammar, and what is in the scope of transformational rules.</Paragraph> <Paragraph position="6"> (ii) We can name empirically or informally the transformational rules such as passive, that deletion, compl~ment/obJect transposition, etc., but to represent these rules formally in the form of (1) without contradiction for all the sentence structures generated from the specified phrase structure grammar, is difficult.</Paragraph> <Paragraph position="7"> (iii) Transformations which accompany the changes in the part of speech or the morphophonemic forms of words are difficult to treat.</Paragraph> <Paragraph position="8"> (iv) A transformational rule can not be applied unconditionally to the structure satisfying the rule form, but there are many cases where the application of rules depend on the semantics of the sentence.</Paragraph> </Section> <Section position="2" start_page="22" end_page="22" type="sub_section"> <SectionTitle> 4.2 Application of transformational rules </SectionTitle> <Paragraph position="0"> For the transformational rules of the type 1, we generate a sentence by the phrase structure grammar and at the same time memorize the generation steps of the sentence by the tree structure representation. Next we apply a transformational rule of the type I to this tree. If the rule is found to fit to the structure, then another tree is constructed from the original tree referring to the transformational rule.</Paragraph> <Paragraph position="1"> Examples of this type are: ~.NP.VT-NPI.~ --~ 1.4.BE-3.BY-2-5 (passive form) This book emphasized the recent development clearly.</Paragraph> <Paragraph position="2"> --* The recent development be emphasize(d) by this book clearly.</Paragraph> <Paragraph position="4"> Last year John became a doctor of philosophy at thirty.</Paragraph> <Paragraph position="5"> --*Last year what do John become at thirty? The application of morphophonemic rules to these transformed sentences are explained in SS 6.</Paragraph> <Paragraph position="6"> For the transformational rules of the type 2, we generate first a sentence by the phrase structure grammar, with its internal tree structure. Then we select a proper phrase name which is a proper branch point of the tree, with the word attached to the phrase name. Next we start the generation of another sentence starting with the phrase name and the corresponding word, which are selected just now. This generation is by the method explained in 3.4. Then the two sentences thus generated have a same word, which is the key point in the usual transformational rules of type 2.</Paragraph> <Paragraph position="7"> An example of this type is illustrated in Fig. 4. This is a combination of two sentences of Fig. I and Fig. 2. The rule applied here is, SS: ~-WT1.NPI-~.CM. NPI.~ ~ 1.2.3.WHICH-7.4 and the generated sentence is Several most number computer already precede specialist into trend which read the paper.</Paragraph> <Paragraph position="8"> This example indicates that a transformational rules can not be applied in every case, even if the structure satisfies the rule form. There are many other examples of this nature.</Paragraph> <Paragraph position="9"> For the transformational rules of the type 3, we have mainly concerned with the noun phrases which are the results of the application of transformational rules to certain phrases, especially to the sentence form SE. For example,</Paragraph> <Paragraph position="11"> Kennedy is the president of the U.S.</Paragraph> <Paragraph position="12"> --~ Kennedy, the president of the U.S., NPI.BE.PP ~ 1-3 Scientists are in the dome of the south pole Scientists in the dome of the south pole. This type of transformational rules are incorporated in the generation by the phrase structure grammar.</Paragraph> <Paragraph position="13"> Another important transformational rules are those which accompany the change in the part of speech of words.</Paragraph> <Paragraph position="14"> For example, VTI.NPI-~ ~ nn -1-PRP-2-3 apply computer to the MT research application of computer to the MT research VT1-NPI.@ ~ nn-l. BE GIVEN T0.2-3 consider the problems of the theory --~ consideration is given to the problems of the theory We have not investigated yet this type of transformational rules except few ones, in which the word dictionary should have information about the interchange of the parts of speech.</Paragraph> </Section> </Section> <Section position="6" start_page="22" end_page="22" type="metho"> <SectionTitle> 5. SEMANTIC CATEGORIES AND THEIR RELATIONSHIP IN SYNTACTIC UNIT </SectionTitle> <Paragraph position="0"> In the generation process thus defined, each word is determined by the selection rule s~--~ w applied to SWC's. How this word selection should be done is the semantics here considered. If the selection is done randomly without any semantic restriction, completely anomalous sentence will appear.</Paragraph> <Paragraph position="1"> To prevent this a new word is to be selected compatible with the already selected words which are in the neighborhood. Such semantic selection of words will especially Be important in the syntactic relations such as subject noun & predicate verb subject noun & predicate verb & complement (or object) adjective modifier & noun noun & noun ! adjective & adjective I (coordination structure) verb & verb etc.</Paragraph> <Paragraph position="2"> Selection of a proper word in relation to the other words will eventually require the semantic notifications to the words and their mutual relationship in a sentence. In other words the system of semantic categories is to be set up and the meanings of all the words are to be represented in the system.</Paragraph> <Paragraph position="3"> The construction of a system of the semantic categories may be done best by the replaceability relation among words in sentences. For example, to the verb &quot;walk&quot;, there is a group of words which can be the subject to the verb &quot;walk&quot;. To the word group thus formed, there will be another word group which can be the predicate and has a verb &quot;walk&quot; as its member. This word classification has not been tried yet on the whole scale, and indeed Sakai & Nagao 9 this is very difficult to do. So we have done a slightly different way, although the fundamental attitude of our word categorization is the replaceahility of words in sentences.</Paragraph> <Paragraph position="4"> We postulate that all the words might be properly characterized by setting up a number of key concepts. For example a word &quot;voyage&quot; is categorized as journey with the additional images such as amusement, time duration, ocean etc. In fact when we speak we actually construct sentences fully aware of such additional meanings.</Paragraph> <Paragraph position="5"> Thus our aim is to extract such word images and to know how these images are mutually connected in such and such sentence structures. So we have started the extraction of semantic categories partly taking into consideration the Roget's thesaurus and some other publications. We have assigned the following numbers to the semantic categories of the parts of speech. 100--299 verb 300--499 noun 500--699 adjective 700--799 adverb 900-- preposition The ten's digit indicates the rough semantic categories in a part of speech and the one's digit is to the further classifications. At present the number of categories for the verbs ia about 40, for the nouns about 90, for the adjectives about 50, etc. For the prepositions we have attached a number to each word. These semantic categories are shown in table I. Next we have to clarify the connectivity of words in a sentence. To do this we have attached several kind of semantic categories to each word in the following way.</Paragraph> <Paragraph position="6"> categories intrinsic to the verb.</Paragraph> <Paragraph position="7"> categories which can modify the verb (additional images of the verb) categories which can stand as subject to the verb.</Paragraph> <Paragraph position="8"> categories which can stand as object or complement to the verb. special prepositions following the verb if any.</Paragraph> <Paragraph position="9"> grammatical indication as to the form of the verb.</Paragraph> <Paragraph position="10"> categories intrinsic to the noun.</Paragraph> <Paragraph position="11"> P2: categories which can modify the noun (additional images of the noun) P3: grammatical indication as to the form of the noun.</Paragraph> <Paragraph position="12"> categories intrinsic to the adjective.</Paragraph> <Paragraph position="13"> categories which can modify the adjective (additional images of the adjective) prepositions following the predicative adjective.</Paragraph> <Paragraph position="14"> categories intrinsic to the adverb.</Paragraph> <Paragraph position="15"> This expresses, for example, that a verb can take a noun for the subject whose semantic c~tegories P1 belong to the P3 of the verb, and can take a noun for the object or complement whose semantic categories PI belong to the P4 of the verb, etc. These are the conditions/~ introduced in 3.3. Examples of words having these connectivity informations are shownin table 2. Sakai & Nagao 10 The generation process is thus first the selection of a verb, and then the determination of subject, object or complement referring to the semantic concordance mentioned here. Therefore each expansion rule of the phrase structure grammar has the indication such as words are to be assigned having the semantic concordance between the pair of categories bracketed by < > . The first element in < > is the category of the phrase to the left of < , and the second element is that of the main constituent. Therefore a word is assigned to NP, whose semantic categories P1 have the same term in the P3 of VTI, and so on.</Paragraph> <Paragraph position="16"> But there are many grammatical phrases where we can not tell what kind of semantic relationship are to be established. We have not attached the semantic relationship to the phrases like, main verb : adverbial phrases preceded by preposition main sentence : subordinate clause noun : its adjectival clause etc.</Paragraph> <Paragraph position="17"> It is also difficult to find out the semantic relationship between the nouns of the form, NO + NO, NO + NO + NO, NO of NO such as, machine translation, information processing machine generation of sentences.</Paragraph> <Paragraph position="18"> However when these phrases are given from suitable transformations of another phrases such as solution of a problem .-.solve a problem, generation of sentences.--, generate sentences, we can establish the semantic relationship of these two noun in the phrase before the transformation is applied. In this case we have to know the noun form of a verb or its vice versa. This information is contained in the word dictionary as P6 for the verb and as P3 for the noun.</Paragraph> <Paragraph position="19"> The semantic relationship here introduced is essentially the connectivity between two words in a phrase, so there is a possibility of generating absurd sentences. To prevent this we have to know more minute mutual influence of meanings among words in a sentence.</Paragraph> </Section> <Section position="7" start_page="22" end_page="22" type="metho"> <SectionTitle> 6. MORPHOPHONEMIC RULES </SectionTitle> <Paragraph position="0"> We want to propose that the morphophonemic rules can be represented by a kind of operators operating on the words in the neighborhood. We include negation action, tense, case etc. to this level. We take the operators such as follows.</Paragraph> <Paragraph position="1"> (not), ~r (present tense), ~s (past tense) inf (infinitive), ~ (third person singular), pl (plural) su'~ (subjective casej, ob~ (objective case) Sakai & Nagao 11 ing (ing-form of a verb), ed (past participle) nn (nominalization of a verb)~- etc.</Paragraph> <Paragraph position="2"> The functions of these operators are, n + verb ~ do + not + verb</Paragraph> <Paragraph position="4"> ps + verb --~ verb (past form) ing + verb--~verb (gerund or present participle) ed + verb --. verb (past participle) etc.</Paragraph> <Paragraph position="5"> Besides these, for the verb BE(R) and HAVE(~), the following three steps are to be applied in this order.</Paragraph> <Paragraph position="6"> (I) ~ + ~ + verb---, be + being + e d + verb (2) ~ + verb---, be + in~ + verb (3) h + be --. have been For example in the generation of a sentence shown in Fig. 5, the sentence obtained initially is # the father sg sub~ ~ enjoy fresh breeze sg obj # Here the following operationsare applied. s_~ oh__/---, ob~ s_~, s_~# ---~ # noun ~ ---. noun, ~ enjoy ~ be + in~ + enjoy in~ + enjoy---~ enjoying, ~ + be ~ have been Sg sub--~ subs~, sg have---~ has noun sub ~ noun And we can get the final form, # the father has been enjoying fresh breeze # These operators can appear both in the phrase structure grammar and in the transformational rules, but the operations of these are supposed to be done after the application of transformational rules. But there occur many complicated situations for the sentences after the application of transformational rules and to what extent we can go on this line remains to be seen in the future.</Paragraph> </Section> class="xml-element"></Paper>