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<Paper uid="J93-1005">
  <Title>Structural Ambiguity and Lexical Relations</Title>
  <Section position="2" start_page="0" end_page="0" type="intro">
    <SectionTitle>
1. Introduction
</SectionTitle>
    <Paragraph position="0"> Prepositional phrase attachment is the canonical case of structural ambiguity, as in the timeworn example: Example 1 I saw the man with the telescope.</Paragraph>
    <Paragraph position="1"> An analysis where the prepositional phrase \[pp with the telescope\] is part of the object noun phrase has the semantics &amp;quot;the man who had the telescope&amp;quot;; an analysis where the PP has a higher attachment (perhaps as daughter of VP) is associated with a semantics where the seeing is achieved by means of a telescope. The existence of such ambiguity raises problems for language models. It looks like it might require extremely complex computation to determine what attaches to what. Indeed, one recent proposal suggests that resolving attachment ambiguity requires the construction of a discourse model in which the entities referred to in a text are represented and reasoned about (Altmann and Steedman 1988). We take this argument to show that reasoning essentially involving reference in a discourse model is implicated in resolving attachment ambiguities in a certain class of cases. If this phenomenon is typical, there is little hope in the near term for building computational models capable of resolving such ambiguities in unrestricted text.</Paragraph>
    <Section position="1" start_page="0" end_page="0" type="sub_section">
      <SectionTitle>
1.1 Structure-Based Ambiguity Resolution
</SectionTitle>
      <Paragraph position="0"> There have been several structure-based proposals about ambiguity resolution in the literature; they are particularly attractive because they are simple and don't demand calculations in the semantic or discourse domains. The two main ones are as follows.</Paragraph>
      <Paragraph position="1"> * Right Association--a constituent tends to attach to another constituent immediately to its right (Kimball 1973).</Paragraph>
      <Paragraph position="2"> * AT&amp;T Bell Laboratories, 600 Mountain Ave., Murray Hill, NJ 07974, USA. f The new affiliation of the second author is: Institut ffir maschinelle Sprachverarbeitung, Universit/it Stuttgart.</Paragraph>
      <Paragraph position="3"> (~) 1993 Association for Computational Linguistics Computational Linguistics Volume 19, Number 1 * Minimal Attachment--a constituent tends to attach to an existing nonterminal using the fewest additional syntactic nodes (Frazier 1978).</Paragraph>
      <Paragraph position="4"> For the particular case we are concerned with, attachment of a prepositional phrase in a verb + object context as in Example 1, these two principles--at least given the version of syntax that Frazier assumes--make opposite predictions: Right Association predicts noun attachment, while Minimal Attachment predicts verb attachment.</Paragraph>
      <Paragraph position="5"> Psycholinguistic work on structure-based strategies is primarily concerned with modeling the time course of parsing and disambiguation, and acknowledges that other information enters into determining a final parse. Still, one can ask what information is relevant to determining a final parse, and it seems that in this domain structure-based disambiguation is not a very good predictor. A recent study of attachment of prepositional phrases in a sample of written responses to a &amp;quot;Wizard of Oz&amp;quot; travel information experiment shows that neither Right Association nor Minimal Attachment accounts for more than 55% of the cases (Whittemore, Ferrara, and Brunner 1990). And experiments by Taraban and McClelland (1988) show that the structural models are not in fact good predictors of people's behavior in resolving ambiguity.</Paragraph>
    </Section>
    <Section position="2" start_page="0" end_page="0" type="sub_section">
      <SectionTitle>
1.2 Resolving Ambiguity through Lexical Associations
</SectionTitle>
      <Paragraph position="0"> Whittemore, Ferrara, and Brunner (1990) found lexical preferences to be the key to resolving attachment ambiguity. Similarly, Taraban and McClelland found that lexical content was key in explaining people's behavior. Various previous proposals for guiding attachment disambiguation by the lexical content of specific words have appeared (e.g. Ford, Bresnan, and Kaplan 1982; Marcus 1980). Unfortunately, it is not clear where the necessary information about lexical preferences is to be found. Jenson and Binot (1987) describe the use of dictionary definitions for disambiguation, but dictionaries are typically rather uneven in their coverage. In the Whittemore, Ferrara, and Brunner study (1990), the judgment of attachment preferences had to be made by hand for the cases that their study covered; no precompiled list of lexical preferences was available. Thus, we are posed with the problem of how we can get a good list of lexical preferences.</Paragraph>
      <Paragraph position="1"> Our proposal is to use co-occurrence of verbs and nouns with prepositions in a large body of text as an indicator of lexical preference. Thus, for example, the preposition to occurs frequently in the context send NP_, that is, after the object of the verb send. This is evidence of a lexical association of the verb send with to. Similarly, from occurs frequently in the context withdrawal_, and this is evidence of a lexical association of the noun withdrawal with the preposition from. This kind of association is a symmetric notion: it provides no indication of whether the preposition is selecting the verbal or nominal head, or vice versa. We will treat the association as a property of the pair of words. It is a separate issue, which we will not be concerned with in the initial part of this paper, to assign the association to a particular linguistic licensing relation. The suggestion that we want to explore is that the association revealed by textual distribution--whether its source is a complementation relation, a modification relation, or something else--gives us information needed to resolve prepositional attachment in the majority of cases.</Paragraph>
    </Section>
  </Section>
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