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<?xml version="1.0" standalone="yes"?> <Paper uid="C90-2042"> <Title>SOLVING AMBIGUITIES IN THE SEMANTIC REPRESENTATION OF TEXTS</Title> <Section position="3" start_page="0" end_page="0" type="concl"> <SectionTitle> 3 241 </SectionTitle> <Paragraph position="0"> its object. Yet the structure of the sentences appears the same. Only by checking the semantic constraints with the directed join algorithm will the right interpretation be given. This is why, in our system, the processing of incomplete syntactic information is done at the level of semantic analysis rather than at the level of syntactic analysis.</Paragraph> <Paragraph position="1"> In this paragraph we group together the solving of the following co-reference problems, since the same resolution method is The solving of a co-reference problem consists in instantiating tile anaphoric element by assigning to it a concept type and possibly a referent which have already been used in the text. In some cases, it is also necessary to have a look-ahead procedure which scans the text forwards.</Paragraph> <Paragraph position="2"> Backward search algorithm In our system, the backward search is done by scanning a LIFO stack of concepts and referents.</Paragraph> <Paragraph position="3"> Before starting to build a Conceptual Graph for the sentence, all the nouns (proper or conln\]on nouns, not preceded by a demonstrative determiner) and anaphors are processed in the order in which they appear in the sentence.</Paragraph> <Paragraph position="4"> We assign to each of the nouns a new referent number (or new set of referents in the case of polysemy) and we store in a LIFO stack the sentence sequence number, tile lemma, the noun Conceptual Graph(s), its referent(s), its gender and number. This processing of nouns is done once and for all, several syntactic analyses giving rise to the same referent number for the same noun at the same place in the sentence.</Paragraph> <Paragraph position="5"> As for the anaphors, the stack is scanned LIFO and gender and number are checked.</Paragraph> <Paragraph position="6"> The result of this search is a set of possible solutions. In fact, the set of possible solutions for an anaphor may be viewed as an &quot;extended polysemy&quot;. For reasons of pragmatism and performance, tile search is limited to a definite number of sentences upward in the text. This number is parameterized and may be specified by the user.</Paragraph> <Paragraph position="7"> When the set of graphs corresponding to an anaphor is linked to its context (e.g. a pronoun subject to a verb), the &quot;best&quot; solutions are chosen by the directed join management algorithm, as explained above in the example of polysemy (&quot;to go from.., to...&quot;). Then the solution corresponding to the most recent entry in the concept stack is selected, to avoid having too many solutions. This is done by way of a projection of the Conceptual Graph contained in the stack into the result of the directed join. However this selection of the most recent solution may backtrack: this is useful if the set of graphs for the anaphor has to be linked several times. (This is the case for coordinated verbs with the same subject, or for infinitives with the same subject as the main verb, for example). In this case, thanks to the directed join management algorithm, the best solution of the whole process is chosen.</Paragraph> <Paragraph position="8"> Example: &quot;Le pilote et le garcon sont arrives hier. II projette de piloter I&quot; avion&quot; (&quot;The pilot and the boy came yesterday. He plans to pilot the plane&quot;) Suppose we have the following entries in the semantic lexicon: garc, on (boy) < PERSON in the lattice avion (plane) < VEHICLE in the lattice</Paragraph> <Paragraph position="10"> The result for the first sentence is: The result for the second sentence is: Forward search algorithm If no solution has been found in the stack with the backward search algorithm, or if the 242 4 solutions round have led to a failure in the linkage to the context, then the forward search algorithm is activated. This is easy since we already have in the stack the information concerning all the nouns of the sentence. If the forward search also leads to a failure, our system simply prompts the user. If no answer is given (or if we are in balch mode), the system instantiates the anaphor to the most general concept in the lattice, which is ENTITY.</Paragraph> <Paragraph position="11"> However, it is not always sufficient to activate the torward search algorithm only in cases of total failure of the backward search algorithm. In fact, some syntactic constructions (corresponding to cataphoric relations) should autornatically start the forward search algorithm, even though there might be some solutions given by the backward search algorithm. Such cataphoric relations may correspond to set expressions that emphasize a word which appears later in tile sentence (at least, in French): &quot;11 marche bien, ce programme&quot; (Literally, &quot;It works well, this program&quot; ). &quot;11&quot; (&quot;it&quot;) refers to &quot;progranlmo&quot; (&quot;program&quot;). Miscellaneous problems related to ~lnaphors tn the case of dernonstrative determiners, Ihe information corresponding 1o the concept type is already given bythe noun. But there may be set expressions for which the noun lollowing the demonstrative does not correspond exactly R) a previous word in the text. I~xarnple: &quot;La hausse du dollar s'est intensifi6e bier ~ Paris. Cette 6volution a provoqu./; ...&quot; (&quot;The rise of the dollar sharpened yesterday in Paris. This change caused ...&quot;) In this case, the search is the stack must not be nlade ac('erding to words: instead, a projection of the Conceptual Graph(s) of the noun (&quot;change&quot;) must be made into 1he Conceptilal Graphs of the stack.</Paragraph> <Paragraph position="12"> For noun ellipses (&quot;another one&quot;, &quot;that of&quot;), the thing to do is to search only for a concept type in the stack, and to assign a new leferent to it. For example, the sentence: &quot;Le d6ficit de t988 est ~.quivatent ~ celui de 1987&quot; (&quot;The deficit of 1988 is equivalent to that of 1987&quot;) gives the following solution: ~..,,~_.I{D E F I C I TT$1 ME. :_ _~ In order to solve possessive pronouns (&quot;theirs&quot;), concept types have to be follnd both for the possessed entity and for the owner, and the two have to be linked together with an appropriate conceptual relation. null Example: &quot;Le garc, on a fait ses devoirs et la fille a fait les siens&quot; (&quot;The boy did his homework and the girl did hers&quot;) A difficult problem is plural anaphors, since they may correspond te several entries in the stack (implicit coordination).</Paragraph> <Paragraph position="13"> Example: &quot;L'homme est arriv6 avec la femme. IIs sont all6s d6jeuner&quot; (&quot;The man arrived with the woman. They went to lunch&quot;).</Paragraph> <Paragraph position="14"> In this case, we either search for a nonsyntactically coordinated plural antecedent, or for a set of antecedents which have a common ancestor in the lattice;, favoring elements which are already syntactically coordinated. This requires storing information concerning syntactic coordination of nouns in the stack.</Paragraph> <Paragraph position="15"> Further to the problem of plural anaphors, it may happen that an anaphoric element is quantified (&quot;those three persons&quot;, &quot;the three of them&quot;, etc.), tn suchacase, and wherever applicable, the referents must be posted upwards until the target sum is reached.</Paragraph> <Paragraph position="16"> In addition, in order to prevent the generation of absurd Conceptual Graphs, pragmatic rules based on syntax are applied. For the resolution of a given anaphor, this processing mainly consists in forbidding the stack entries whose syntactic structures in the sentence are incompatible with the syntactic structure of the anaphor \[4\]. (For example, a possessive determiner cannol refer te the possessed entity).</Paragraph> <Paragraph position="17"> The semantic coherence checking algorithm We have seen that the directed join and directed join management algorithms are useful in solving polysemy, incomplete syntactic information and anaphors. But this is not sufficient, because these problems may be inter-related. For example, we may have co-ordinated verbs with the same subject, this subject being polysemous, or- even worse, a pronoun. We may also want to carry the 5 243 polysemous or pronoun subject of a main verb over to its infinitive complement.</Paragraph> <Paragraph position="18"> In such cases, we have to check that the same solution for the subject has been taken everywhere in the resulting Conceptual Graph. This is the purpose of the semantic coherence checking algorithm. First, it ensures that different polysemous entries of one occurrence of a word in the sentence do not appear in the final result for the sentence. Secondly, it checks that the same solution for a pronoun has been selected throughout the processing. In cases of failure, the backtrack is activated. The backtrack on a pronoun is cut as soon as a satisfactory solution is found. This semantic coherence checking algorithnl uses lhe projection algorithm.</Paragraph> <Paragraph position="19"> Conclusion Our prototype is still under development, and we do not claim to have solved all the ambiguities which can be found in Natural Language. However the Conceptual Graph model, along with the appropriate algorithms, has proven to be useful for the resolution of ambiguities wtlich occur most often in real texts.</Paragraph> <Paragraph position="20"> As far as the treatment of anaphors is concerned, we plan to extend it, as follows: * The search for a referent will be applied to every proper noun and to every common noun preceded by a definite article, in order to introduce more cohesion in the representation of the text. (&quot;Mr John Akers, manager of IBM ... Mr Akers ...</Paragraph> <Paragraph position="21"> John ... the manager&quot;).</Paragraph> <Paragraph position="22"> * But, in order to avoid wrong interpretations, the local context of a noun (i.e. its qualifiers) will then be stored in the stack of concepts and referents. This should also allow the solving of qualified noun ellipses (&quot;the red one&quot;), but the problem of the scope of a local context then arises.</Paragraph> <Paragraph position="23"> * The solving of anaphors referring to statements is theoretically feasible with the Conceptual Graph model, by the use of conceptual pointers between PROPOSITIONS. null * The resolution of anaphors within long quotations, which introduce a context change, should take the context change into account.</Paragraph> <Paragraph position="24"> Finally, sonle ambiguities may only be solved by the application of rules of common sense and/or deduction. A deductive component has been implemented in our system \[6\] \[2\]. This deductive component, applying appropriate production rules, should be invoked either during the text processing, or as post-processing on the set of Conceptual Graphs for a text.</Paragraph> </Section> class="xml-element"></Paper>