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<Paper uid="C92-3141">
  <Title>HIGH-PROBABILITY SYNTACTIC LINKS</Title>
  <Section position="2" start_page="0" end_page="0" type="intro">
    <SectionTitle>
1 Introduction
</SectionTitle>
    <Paragraph position="0"> In this paper we consider syntactic relations between words of a sentence that can be strongly predicted by local mechanisms. For instance, if a sentence contains a pair of words ... red block ....</Paragraph>
    <Paragraph position="1"> then the reader immediately makes a conjecture that red is an adjective modifier for the noun block. The same is true for semantically abnormal pairs such as ... green ideas ....</Paragraph>
    <Paragraph position="2"> Other examples of strong prediction are provided by pairs ... authors describe ....</Paragraph>
    <Paragraph position="3"> ... problem is..., for which a &amp;quot;subject - verb&amp;quot; relation takes place with high probability.</Paragraph>
    <Paragraph position="4"> In most cases, such simple hypotheses prove to be correct. However, sometimes they lead to errors, as for the pair problem is in the sentence (I) The solution of this problem is very simple. In this example, however, by the moment the word is has been read, the word problem is already engaged in other strongly predicted constructions, namely the prepositional phrase of&amp;quot; this problem and even the whole noun phrase the solution of this problem. A conflict arises, and plausibility of the new hypothesis becomes much lower.</Paragraph>
    <Paragraph position="5"> Such syntactic relations may concern not only adjacent words. For instance, in (1) it is for the pair solution ... is that the &amp;quot;subject - verb&amp;quot; relation will be conjectured.</Paragraph>
    <Paragraph position="6"> In this paper, slrong prediction of syntactic relations is modeled within the framework of dependency syntax (see Mel'~uk 1974, 1988). According to this theory, (surface) syntactic structure of a sentence is an oriented tree whose nodes are the words of the sentence (more precisely, their lexico-morphological interpretations). The arcs of the tree represent syntactic links between words and are labeled by names of syntactic relations. The result of strong prediction is a partial parse of the sentence, in which high-probability syntactic links are established. In our opinion, dependency structures are better adapted to partial parsing than constituent structures. The reason is that the dependency structure of a segment is the same both when the segment is considered as isolated and when it is considered as a part of some sentence (by &amp;quot;segment&amp;quot; we understand any sequence of words). Generally, this is not true for constituent structures. For instance, the segment l saw a man has the dependency structure * (2) l-compl pred \[ det 1</Paragraph>
    <Paragraph position="8"> both as a complete sentence and as a part of the sentence I saw a man with a telescope. The fact that the latter sentence is ambiguous does not hamper anything, as both its structures contain subtree (2) (and differ only in arcs that go into the word with):  On the other hand, the constituent structure of the segment I saw a man is not fully inherited in the constituent structures of the longer sentence. In our opinion, this comparison demonstrates that, in a certain sense, dependency structures reflect the incremental nature of sentence comprehension from left to right better than constituent structures do.</Paragraph>
    <Paragraph position="9"> In this paper we describe a bottom-up, left-to-right algorithm of partial parsing that establishes high-probability syntactic links. It is implemented on a VAX 11/750 computer as a subsystem of a multipurpose linguistic processor developed in the Laboratory of Computational Linguistics of the Institute for Problems of Information Transmission, the Russian Academy of Sciences (Apresjan et al. 1992). The partial parser is employed as a preprocessing unit before the operation of the main filter-type parser. It can also be used for automatic indexing and lemmatization.</Paragraph>
    <Paragraph position="10"> The algorithm is language-independent: all language-specific information is recorded in the dictionaries and the rules that establish links.</Paragraph>
    <Paragraph position="11"> * Full names of English syntactic relationS that appear in example= are: predicative, determinative, lsl completive, prepositional, attributive, adverbial. The number of relations used In complete models of English and Ru~tan syntax varies from 40 to  1974; Mel'~.uk and Pertsov 1987; Apresjan et al. 1989, 1992). AcrEs DE COLING-92, NANT~, 23-28 AOtJT 1992 9 3 0 PROC. OF COLING-92. NANTES, AUG. 23-28. 1992 Experiments with Russian sentences have given promising results: on average, the algorithm establishes 70 - 80 ~o of syntactic links of a sentence; processing speed (exclusive of morphological analysis) is about 10 words per CPU second. The error rate is less than 1% (stable estimates have not been obtained yet).</Paragraph>
  </Section>
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