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<Paper uid="W99-0112">
  <Title>Reference Hashed</Title>
  <Section position="3" start_page="100" end_page="102" type="intro">
    <SectionTitle>
2 Background
</SectionTitle>
    <Paragraph position="0"> It has been commonly agreed that a discourse is hierarchically organised. However. this is already the lowest common denominator among current approaches to discourse grammars and text comprehension. There is a wide range of views of what a formal representation of a discourse should look like. The following sections give a short introduction to two suands of research concerned with discourse processing. The first one, DRT and followers, is a linguistically-oriented approach that. generally speaking, captures the hierarchical structure of a discourse by a tree-like representation. The second strand, based on CT, is motivated by psychological experiments and models the structure of a discourse as a list representation of possible discourse referents. Further developments of CT have employed a stack structure or a cache storage.</Paragraph>
    <Section position="1" start_page="100" end_page="100" type="sub_section">
      <SectionTitle>
2.1 Hierarchical discourse grammars
</SectionTitle>
      <Paragraph position="0"> SDRT (and RST) assume that so-called discourse (or rhetorical) relations are the links between discourse segments. A discourse relation has to be derived in order to achieve a coherent discourse. More importantly, the choice of this relation has a crucial influence on possible antecedents for anaphoric expressions, z Asher (i 993) defines in SDRT the terms subordination and openness that specify where open attachment sites are in a discourse structure. A tree-like representation illustrates the hierarchical structure of the discourse. Basically, the nodes on the so-called &amp;quot;right frontier&amp;quot; of the discourse structure are assumed to be available for further attachment (Webber. 199 i ).</Paragraph>
      <Paragraph position="1"> Generally speaking, all nodes which dominate the current node of the newly processed sentence are open (i.e.D.Subordination). However, a restriction is introduced by the term D.Freedom which applies to all nodes that are directly dominated by a topic (i.e. ~ ~/3), unless it is the current node (see figure 1). An informal definition for possible attachment sites looks like the following: I. The last clause represented as a Discourse Rep- null resentation Structure (DRS) K.</Paragraph>
      <Paragraph position="2"> 2. Any DRSs that are embedded in K.</Paragraph>
      <Paragraph position="3"> 3. Any DRSs that dominate the DRSs in I. and 2.</Paragraph>
      <Paragraph position="4"> through Explanation, Elaboration or ~\[</Paragraph>
      <Paragraph position="6"> SDgr exploits discourse relations to establish a hierachical ordering of discourse segments. A so-called constituent graph indicates the dependencies Zl will concentrate on how SORT deals xvith this i.,~ue in the folltm, ing. A study that .shows how RST can be u.~d to make predictions regarding anaphora resolution in a text can be found in Fox (1987).</Paragraph>
      <Paragraph position="7"> between ~cgments,e.,~pecially highlighting the ()pen attachment pt&gt;h\]ls.</Paragraph>
      <Paragraph position="8"> SDRT has been sucessful whet) phenomena are considered thai are explainable because of the hierarchical structure of the discourse. This approach is too restrictive when an anaphoric reference is drawn over .~egment. boundaries:  (I) (a) Mary once organised a party..(b) Tqm  bought the beer. (c) Pete~&amp;quot; was in charge of the food. (d) Years later Mary still complained that it was too spicy.</Paragraph>
      <Paragraph position="9"> The sentence (Id) continues at the top level of the discourse, but the antecedent of it (i.e. food) is still available even though it is deeply embedded in an Elaboruzirm segmenr(i.e. (! a-c)).</Paragraph>
      <Paragraph position="10"> Other shortcomings concern formal, features.</Paragraph>
      <Paragraph position="11"> First,&amp;quot; SDRT is not capable Of expressing under-specification for ambiguous sequences. Second, the derivation of the di~'~turse structure is not monotonic. Once derived, SDRSs are overwritten by an uLulate.</Paragraph>
    </Section>
    <Section position="2" start_page="100" end_page="102" type="sub_section">
      <SectionTitle>
2.2 Centering
</SectionTitle>
      <Paragraph position="0"> CT proposed by Grosz et al. (1995) offers a text comprehension model that describes the relation between the focus of attention and the choices of referring expressions within a discourse segment. The main idea of this theory is that a sentence possesses a center arid that normally one Continues to write (or talk) about this center. Each utterance 0~ gets a list of forward-looking centers C/(U~) assigned to it. Basically, all the entities mentioned by the sentence are ranked according to their degree of being in the center of the utterance. Each sentence also has a unique backward.looking center C'b(Ui). A main claim by the theory is that the most likely C6(Ui+t) is the most highly ranked Cl(\[/i)~ Hence, the criteria for ranking the entities on the forward-looking center list are crucial for the predicative power of this theory. No tm~ly, the grammatical relations subject, object etc. determine the preferred Cp(Ui) (i.e. the first entity on the Cl(Ui ) list).</Paragraph>
      <Paragraph position="1"> As mentioned earlier in this section, the initial account to centering is only concerned with the choice of referring expressions within a discourse segment.</Paragraph>
      <Paragraph position="2"> Since a more general theory to referring expressions is needed, an extension is presented by Grosz and Sidner (1986). They use a stack mechanism for representing the different discourse segments. If one segment is closed off. the information regarding the  forward- and backward looking centers is popped off the stack. The new top clement of the stack contains the centering information from the old segment that the subsequent discourse continues with.</Paragraph>
      <Paragraph position="3"> This simple stack mechanism has been criticised.</Paragraph>
      <Paragraph position="4"> In particular Walker (1998) points out that (i) a long intervening discourse segment Can make it difficult to return back to earlier mentioned discourse referents and (ii) discourse referents introduced in a subordinated segment can easily be carded over to a higher segment (e.g. (I)). Note that a stack model would discard the information of a closed-off discourse segment. Walker proposes acache storage that keeps often-used discourse referents within a storage. If reference is made to an antecedent mentioned earlier in the discourse the information is restored from long term memory.</Paragraph>
      <Paragraph position="5"> Unfortunately, it is not quite clear how this retrieval operation can be fonnalised. In addition, it should be acknowledged that there are structured constraints of the discourse structure that do not allow the choosing of a recently mentioned referent.</Paragraph>
      <Paragraph position="6"> Data discussed within DRT, such as the sentence below, have been presented as evidence for a notion of (in-)accesibility. 3 Negation is a standard example that does not allow a reference to a discourse entity in the prevous sentence: (2) No man walks in the park. #He whistles.</Paragraph>
      <Paragraph position="7"> In the given example sequences the pronoun he cannot refer back to the discourse refett~ts introduced inthe previous sentence. Another example can be found in (3) that involves a conditional:  (3) If a farmer owns a donkey, he beats it. #He hates it.</Paragraph>
      <Paragraph position="8">  Again, neither a pronominal reference by he nor by it is possible. It may be concluded from these data that a cache approach is not restrictive enough. The discussion so far has shown that the data structures used for discourse processing are either too restrictive or not restrictive enough. The next Section presents a novel way of representing dis: course referents introduced by a text. The data structure pre.sented is called a hashing list and allows for an efficient way to access stored information. null &amp;quot;Gordon et al. (1998), for example, blend DRT with CT.</Paragraph>
    </Section>
  </Section>
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