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<Paper uid="E87-1036">
  <Title>Buitding Expert Systems. Addison-Wesley Publishing</Title>
  <Section position="3" start_page="0" end_page="218" type="intro">
    <SectionTitle>
1 |RTROOUCT|OB
</SectionTitle>
    <Paragraph position="0"> The development of our computational model for dependency parsing has progressed in three parallel and interrelated phases:  (1) The development of a perspicuous high Level grammar specification Language which grasps well regularities and idiosyncracies of inflectional free word order Languages.</Paragraph>
    <Paragraph position="1"> (2) The acquisition of a grammar using that Language as the description media.</Paragraph>
    <Paragraph position="2"> (3) The development of a parsing strategy and a  compiler for the specification Language. In our first approach the parsing process is described as a sequence of tocat decisions (Netimarkka et at. 1984). A pair of adjacent structures of an input sentence is connected if there exists a valid binary dependency relation between them. Binary relations are boolean expressions of the morphological and syntactic restrictions on argument structures. In that first version dependency sructures were modelled procedurally with finite two-way automata (Lehtota et at. 1985). Grammar descriptions turned out to be complicated to handle, and due to purely Local decisions some gtobat phenomena, such as tong-distance dependencies, were not analyzed.</Paragraph>
    <Paragraph position="3"> A new grammar description formalism and computational method was developed: a declarative high Level Language FUMDPL (J~ppinen et at. 1986) for a grammar, and an underlying blackboard-based parsing method (Vatkonen and Lehtota, 1986). Recently, we have augmented the dependency parsing model to cover also tong-distance dependencies. According to the augmented model we have implemented a blackboard-based dependency parser ADP (Augmented Dependency Parser). In this paper we shortly describe our model and focus on the parsing strategy. For the grammar development environment and the compilation of the high \[ever description Language* see Lehtota et at. (1985 e 1986).</Paragraph>
    <Paragraph position="4"> Our parsing method belongs to the class of constraint systems: a user specifies the constraints holding in the problem domain, and a goat for the computation. The interpreter must search for the goal. The result follows indirectly from the search process, in our model binary relations specify constraints on argument structures. The goal is to find a matching Local environment description for each word of an input sentence. As a side effect of the recognition corresponding partial dependency trees are built. The partial dependency trees ere Linked into a parse tree covering the whole sentence (Figure 1).</Paragraph>
    <Paragraph position="5">  partial dependency trees.</Paragraph>
  </Section>
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